{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Python Machine Learning 3rd Edition* by [Sebastian Raschka](https://sebastianraschka.com) & [Vahid Mirjalili](http://vahidmirjalili.com), Packt Publishing Ltd. 2019\n",
    "\n",
    "Code Repository: https://github.com/rasbt/python-machine-learning-book-3rd-edition\n",
    "\n",
    "Code License: [MIT License](https://github.com/rasbt/python-machine-learning-book-3rd-edition/blob/master/LICENSE.txt)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Chapter 14: Going Deeper -- the Mechanics of TensorFlow (Part 1/3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the optional watermark extension is a small IPython notebook plugin that I developed to make the code reproducible. You can just skip the following line(s)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sebastian Raschka & Vahid Mirjalili \n",
      "last updated: 2019-12-06 \n",
      "\n",
      "numpy 1.17.4\n",
      "scipy 1.3.1\n",
      "matplotlib 3.1.0\n",
      "tensorflow 2.0.0\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -a \"Sebastian Raschka & Vahid Mirjalili\" -u -d -p numpy,scipy,matplotlib,tensorflow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import Image\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The key features of TensorFlow\n",
    "\n",
    "### TensorFlow's computation graphs: migrating to TensorFlow v2\n",
    "\n",
    "### Understanding computation graphs\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 3,
     "metadata": {
      "image/png": {
       "width": 500
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(filename='images/01.png', width=500)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating a graph in TensorFlow v1.x\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Result: z = 1\n",
      "Result: z = 1\n"
     ]
    }
   ],
   "source": [
    "## TF-v1.x style\n",
    "\n",
    "g = tf.Graph()\n",
    "with g.as_default():\n",
    "    a = tf.constant(1, name='a')\n",
    "    b = tf.constant(2, name='b')\n",
    "    c = tf.constant(3, name='c')\n",
    "    z = 2*(a - b) + c\n",
    "    \n",
    "with tf.compat.v1.Session(graph=g) as sess:\n",
    "    print('Result: z =', sess.run(z))\n",
    "    print('Result: z =', z.eval())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Migrating a graph to TensorFlow v2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Result: z = 1\n"
     ]
    }
   ],
   "source": [
    "## TF v2 style\n",
    "a = tf.constant(1, name='a')\n",
    "b = tf.constant(2, name='b')\n",
    "c = tf.constant(3, name='c')\n",
    "\n",
    "z = 2*(a - b) + c\n",
    "tf.print('Result: z =', z)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loading input data into a model: TensorFlow v1.x style"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Result: z = 1\n"
     ]
    }
   ],
   "source": [
    "## TF-v1.x style\n",
    "g = tf.Graph()\n",
    "with g.as_default():\n",
    "    a = tf.compat.v1.placeholder(shape=None, dtype=tf.int32, name='tf_a')\n",
    "    b = tf.compat.v1.placeholder(shape=None, dtype=tf.int32, name='tf_b')\n",
    "    c = tf.compat.v1.placeholder(shape=None, dtype=tf.int32, name='tf_c')\n",
    "    z = 2*(a - b) + c\n",
    "    \n",
    "with tf.compat.v1.Session(graph=g) as sess:\n",
    "    feed_dict = {a:1, b:2, c:3}\n",
    "    print('Result: z =', sess.run(z, feed_dict=feed_dict))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loading input data into a model: TensorFlow v2 style"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Scalar Inputs: 1\n",
      "Rank 1 Inputs: [1]\n",
      "Rank 2 Inputs: [[1]]\n"
     ]
    }
   ],
   "source": [
    "## TF-v2 style\n",
    "def compute_z(a, b, c):\n",
    "    r1 = tf.subtract(a, b)\n",
    "    r2 = tf.multiply(2, r1)\n",
    "    z = tf.add(r2, c)\n",
    "    return z\n",
    "\n",
    "tf.print('Scalar Inputs:', compute_z(1, 2, 3))\n",
    "tf.print('Rank 1 Inputs:', compute_z([1], [2], [3]))\n",
    "tf.print('Rank 2 Inputs:', compute_z([[1]], [[2]], [[3]]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Improving computational performance with function decorators"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Scalar Inputs: 1\n",
      "Rank 1 Inputs: [1]\n",
      "Rank 2 Inputs: [[1]]\n"
     ]
    }
   ],
   "source": [
    "@tf.function\n",
    "def compute_z(a, b, c):\n",
    "    r1 = tf.subtract(a, b)\n",
    "    r2 = tf.multiply(2, r1)\n",
    "    z = tf.add(r2, c)\n",
    "    return z\n",
    "\n",
    "tf.print('Scalar Inputs:', compute_z(1, 2, 3))\n",
    "tf.print('Rank 1 Inputs:', compute_z([1], [2], [3]))\n",
    "tf.print('Rank 2 Inputs:', compute_z([[1]], [[2]], [[3]]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rank 1 Inputs: [1]\n",
      "Rank 1 Inputs: [1 2]\n"
     ]
    }
   ],
   "source": [
    "@tf.function(input_signature=(tf.TensorSpec(shape=[None], dtype=tf.int32),\n",
    "                              tf.TensorSpec(shape=[None], dtype=tf.int32),\n",
    "                              tf.TensorSpec(shape=[None], dtype=tf.int32),))\n",
    "def compute_z(a, b, c):\n",
    "    r1 = tf.subtract(a, b)\n",
    "    r2 = tf.multiply(2, r1)\n",
    "    z = tf.add(r2, c)\n",
    "    return z\n",
    "\n",
    "tf.print('Rank 1 Inputs:', compute_z([1], [2], [3]))\n",
    "tf.print('Rank 1 Inputs:', compute_z([1, 2], [2, 4], [3, 6]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```python\n",
    "## we expect this to result in an error\n",
    "tf.print('Rank 2 Inputs:', compute_z([[1], [2]], [[2], [4]], [[3], [6]]))\n",
    "\n",
    "\n",
    "## >> Error:\n",
    "#ValueError: Python inputs incompatible with input_signature: \n",
    "#inputs (([[1], [2]], [[2], [4]], [[3], [6]])), input_signature \n",
    "#((TensorSpec(shape=(None,), dtype=tf.int32, name=None), \n",
    "#  TensorSpec(shape=(None,), dtype=tf.int32, name=None), \n",
    "#  TensorSpec(shape=(None,), dtype=tf.int32, name=None)))\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TensorSpec(shape=(None,), dtype=tf.int32, name=None)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.TensorSpec(shape=[None], dtype=tf.int32)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## TensorFlow Variable objects for storing and updating model parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<tf.Variable 'var_a:0' shape=() dtype=float32, numpy=3.14>\n",
      "<tf.Variable 'var_b:0' shape=(3,) dtype=int32, numpy=array([1, 2, 3], dtype=int32)>\n",
      "<tf.Variable 'Variable:0' shape=(2,) dtype=bool, numpy=array([ True, False])>\n",
      "<tf.Variable 'Variable:0' shape=(1,) dtype=string, numpy=array([b'abc'], dtype=object)>\n"
     ]
    }
   ],
   "source": [
    "a = tf.Variable(initial_value=3.14, name='var_a')\n",
    "b = tf.Variable(initial_value=[1, 2, 3], name='var_b')\n",
    "c = tf.Variable(initial_value=[True, False], dtype=tf.bool)\n",
    "d = tf.Variable(initial_value=['abc'], dtype=tf.string)\n",
    "print(a)\n",
    "print(b)\n",
    "print(c)\n",
    "print(d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.trainable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "False\n"
     ]
    }
   ],
   "source": [
    "w = tf.Variable([1, 2, 3], trainable=False)\n",
    "\n",
    "print(w.trainable)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<tf.Variable 'UnreadVariable' shape=(3,) dtype=int32, numpy=array([3, 1, 4], dtype=int32)>\n",
      "tf.Tensor([5 0 6], shape=(3,), dtype=int32)\n"
     ]
    }
   ],
   "source": [
    "print(w.assign([3, 1, 4], read_value=True))\n",
    "w.assign_add([2, -1, 2], read_value=False)\n",
    "\n",
    "print(w.value())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-0.722795904 1.01456821 0.251808226]\n"
     ]
    }
   ],
   "source": [
    "tf.random.set_seed(1)\n",
    "init = tf.keras.initializers.GlorotNormal()\n",
    "\n",
    "tf.print(init(shape=(3,)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0.28982234 -0.782292783 -0.0453658961]\n",
      " [0.960991383 -0.120003454 0.708528221]]\n"
     ]
    }
   ],
   "source": [
    "v = tf.Variable(init(shape=(2, 3)))\n",
    "tf.print(v)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "All module variables:  [TensorShape([2, 3]), TensorShape([1, 2])]\n",
      "Trainable variable:    [TensorShape([2, 3])]\n"
     ]
    }
   ],
   "source": [
    "class MyModule(tf.Module):\n",
    "    def __init__(self):\n",
    "        init = tf.keras.initializers.GlorotNormal()\n",
    "        self.w1 = tf.Variable(init(shape=(2, 3)), trainable=True)\n",
    "        self.w2 = tf.Variable(init(shape=(1, 2)), trainable=False)\n",
    "                \n",
    "m = MyModule()\n",
    "print('All module variables: ', [v.shape for v in m.variables])\n",
    "print('Trainable variable:   ', [v.shape for v in\n",
    "                                 m.trainable_variables])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Variables with tf.function"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```python\n",
    "\n",
    "## this will produce an error\n",
    "## ==> you cannot create a varibale inside a\n",
    "##     decorated function\n",
    "\n",
    "@tf.function\n",
    "def f(x):\n",
    "    w = tf.Variable([1, 2, 3])\n",
    "\n",
    "f([1])\n",
    "\n",
    "## ==> results in error\n",
    "## ValueError: tf.function-decorated function tried to create variables on non-first call.\n",
    "\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[3.8610158]\n",
      " [2.94593048]\n",
      " [3.82629013]]\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "\n",
    "tf.random.set_seed(1)\n",
    "w = tf.Variable(tf.random.uniform((3, 3)))\n",
    "\n",
    "@tf.function\n",
    "def compute_z(x):    \n",
    "    return tf.matmul(w, x)\n",
    "\n",
    "x = tf.constant([[1], [2], [3]], dtype=tf.float32)\n",
    "tf.print(compute_z(x))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Computing gradients via automatic differentiation and GradientTape\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Computing the gradients of the loss with respect to trainable variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True True\n",
      "dL/dw :  -0.559999764\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "\n",
    "w = tf.Variable(1.0)\n",
    "b = tf.Variable(0.5)\n",
    "print(w.trainable, b.trainable)\n",
    "\n",
    "x = tf.convert_to_tensor([1.4])\n",
    "y = tf.convert_to_tensor([2.1])\n",
    "\n",
    "with tf.GradientTape() as tape:\n",
    "    z = tf.add(tf.multiply(w, x), b)\n",
    "    loss = tf.reduce_sum(tf.square(y - z))\n",
    "\n",
    "dloss_dw = tape.gradient(loss, w)\n",
    "\n",
    "tf.print('dL/dw : ', dloss_dw)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-0.559999764]\n"
     ]
    }
   ],
   "source": [
    "# verifying the computed gradient\n",
    "#tf.print(-2*x * (-b - w*x + y))\n",
    "\n",
    "tf.print(2*x * ((w*x + b) - y))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Computing gradients with respect to non-trainable tensors\n",
    "\n",
    " Monitoring the non-trainable tensors via `tape.watch()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dL/dx: [-0.399999857]\n"
     ]
    }
   ],
   "source": [
    "with tf.GradientTape() as tape:\n",
    "    tape.watch(x)\n",
    "    z = tf.add(tf.multiply(w, x), b)\n",
    "    loss = tf.square(y - z)\n",
    "\n",
    "dloss_dx = tape.gradient(loss, x)\n",
    "\n",
    "tf.print('dL/dx:', dloss_dx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-0.399999857]\n"
     ]
    }
   ],
   "source": [
    "# verifying the computed gradient\n",
    "tf.print(2*w * ((w*x + b) - y))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Keeping resources for multiple gradient computations \n",
    "\n",
    "via `persistent=True`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dL/dw: -0.559999764\n",
      "dL/db: -0.399999857\n"
     ]
    }
   ],
   "source": [
    "with tf.GradientTape(persistent=True) as tape:\n",
    "    z = tf.add(tf.multiply(w, x), b)\n",
    "    loss = tf.reduce_sum(tf.square(y - z))\n",
    "\n",
    "dloss_dw = tape.gradient(loss, w)\n",
    "dloss_db = tape.gradient(loss, b)\n",
    "\n",
    "tf.print('dL/dw:', dloss_dw)\n",
    "tf.print('dL/db:', dloss_db)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Updating variables: `optimizer.apply_gradients()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Updated w: 1.0056\n",
      "Updated bias: 0.504\n"
     ]
    }
   ],
   "source": [
    "optimizer = tf.keras.optimizers.SGD()\n",
    "\n",
    "optimizer.apply_gradients(zip([dloss_dw, dloss_db], [w, b]))\n",
    "\n",
    "tf.print('Updated w:', w)\n",
    "tf.print('Updated bias:', b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simplifying implementations of common architectures via the Keras API\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "dense (Dense)                multiple                  80        \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              multiple                  544       \n",
      "=================================================================\n",
      "Total params: 624\n",
      "Trainable params: 624\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model = tf.keras.Sequential()\n",
    "model.add(tf.keras.layers.Dense(units=16, activation='relu'))\n",
    "model.add(tf.keras.layers.Dense(units=32, activation='relu'))\n",
    "\n",
    "## late variable creation\n",
    "model.build(input_shape=(None, 4))\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dense/kernel:0       True (4, 16)\n",
      "dense/bias:0         True (16,)\n",
      "dense_1/kernel:0     True (16, 32)\n",
      "dense_1/bias:0       True (32,)\n"
     ]
    }
   ],
   "source": [
    "## printing variables of the model\n",
    "for v in model.variables:\n",
    "    print('{:20s}'.format(v.name), v.trainable, v.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Configuring layers\n",
    "\n",
    " * Keras Initializers `tf.keras.initializers`: https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/keras/initializers  \n",
    " * Keras Regularizers `tf.keras.regularizers`: https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/keras/regularizers  \n",
    " * Activations `tf.keras.activations`: https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/keras/activations  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_1\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "dense_2 (Dense)              multiple                  80        \n",
      "_________________________________________________________________\n",
      "dense_3 (Dense)              multiple                  544       \n",
      "=================================================================\n",
      "Total params: 624\n",
      "Trainable params: 624\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model = tf.keras.Sequential()\n",
    "\n",
    "model.add(\n",
    "    tf.keras.layers.Dense(\n",
    "        units=16, \n",
    "        activation=tf.keras.activations.relu,\n",
    "        kernel_initializer=tf.keras.initializers.GlorotNormal(),\n",
    "        bias_initializer=tf.keras.initializers.Constant(2.0)\n",
    "    ))\n",
    "\n",
    "model.add(\n",
    "    tf.keras.layers.Dense(\n",
    "        units=32, \n",
    "        activation=tf.keras.activations.sigmoid,\n",
    "        kernel_regularizer=tf.keras.regularizers.l1\n",
    "    ))\n",
    "\n",
    "model.build(input_shape=(None, 4))\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Compiling a model\n",
    "\n",
    " * Keras Optimizers `tf.keras.optimizers`:  https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/keras/optimizers\n",
    " * Keras Loss Functins `tf.keras.losses`: https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/keras/losses\n",
    " * Keras Metrics `tf.keras.metrics`: https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/keras/metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.compile(\n",
    "    optimizer=tf.keras.optimizers.SGD(learning_rate=0.001),\n",
    "    loss=tf.keras.losses.BinaryCrossentropy(),\n",
    "    metrics=[tf.keras.metrics.Accuracy(), \n",
    "             tf.keras.metrics.Precision(),\n",
    "             tf.keras.metrics.Recall(),])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Solving an XOR classification problem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tf.random.set_seed(1)\n",
    "np.random.seed(1)\n",
    "\n",
    "x = np.random.uniform(low=-1, high=1, size=(200, 2))\n",
    "y = np.ones(len(x))\n",
    "y[x[:, 0] * x[:, 1]<0] = 0\n",
    "\n",
    "x_train = x[:100, :]\n",
    "y_train = y[:100]\n",
    "x_valid = x[100:, :]\n",
    "y_valid = y[100:]\n",
    "\n",
    "fig = plt.figure(figsize=(6, 6))\n",
    "plt.plot(x[y==0, 0], \n",
    "         x[y==0, 1], 'o', alpha=0.75, markersize=10)\n",
    "plt.plot(x[y==1, 0], \n",
    "         x[y==1, 1], '<', alpha=0.75, markersize=10)\n",
    "plt.xlabel(r'$x_1$', size=15)\n",
    "plt.ylabel(r'$x_2$', size=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_2\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "dense_4 (Dense)              (None, 1)                 3         \n",
      "=================================================================\n",
      "Total params: 3\n",
      "Trainable params: 3\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model = tf.keras.Sequential()\n",
    "model.add(tf.keras.layers.Dense(units=1, \n",
    "                                input_shape=(2,), \n",
    "                                activation='sigmoid'))\n",
    "\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.compile(optimizer=tf.keras.optimizers.SGD(),\n",
    "              loss=tf.keras.losses.BinaryCrossentropy(),\n",
    "              metrics=[tf.keras.metrics.BinaryAccuracy()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "hist = model.fit(x_train, y_train, \n",
    "                 validation_data=(x_valid, y_valid), \n",
    "                 epochs=200, batch_size=2, verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from mlxtend.plotting import plot_decision_regions\n",
    "\n",
    "history = hist.history\n",
    "\n",
    "fig = plt.figure(figsize=(16, 4))\n",
    "ax = fig.add_subplot(1, 3, 1)\n",
    "plt.plot(history['loss'], lw=4)\n",
    "plt.plot(history['val_loss'], lw=4)\n",
    "plt.legend(['Train loss', 'Validation loss'], fontsize=15)\n",
    "ax.set_xlabel('Epochs', size=15)\n",
    "\n",
    "ax = fig.add_subplot(1, 3, 2)\n",
    "plt.plot(history['binary_accuracy'], lw=4)\n",
    "plt.plot(history['val_binary_accuracy'], lw=4)\n",
    "plt.legend(['Train Acc.', 'Validation Acc.'], fontsize=15)\n",
    "ax.set_xlabel('Epochs', size=15)\n",
    "\n",
    "ax = fig.add_subplot(1, 3, 3)\n",
    "plot_decision_regions(X=x_valid, y=y_valid.astype(np.integer),\n",
    "                      clf=model)\n",
    "ax.set_xlabel(r'$x_1$', size=15)\n",
    "ax.xaxis.set_label_coords(1, -0.025)\n",
    "ax.set_ylabel(r'$x_2$', size=15)\n",
    "ax.yaxis.set_label_coords(-0.025, 1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_3\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "dense_5 (Dense)              (None, 4)                 12        \n",
      "_________________________________________________________________\n",
      "dense_6 (Dense)              (None, 4)                 20        \n",
      "_________________________________________________________________\n",
      "dense_7 (Dense)              (None, 4)                 20        \n",
      "_________________________________________________________________\n",
      "dense_8 (Dense)              (None, 1)                 5         \n",
      "=================================================================\n",
      "Total params: 57\n",
      "Trainable params: 57\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "tf.random.set_seed(1)\n",
    "\n",
    "model = tf.keras.Sequential()\n",
    "model.add(tf.keras.layers.Dense(units=4, input_shape=(2,), activation='relu'))\n",
    "model.add(tf.keras.layers.Dense(units=4, activation='relu'))\n",
    "model.add(tf.keras.layers.Dense(units=4, activation='relu'))\n",
    "model.add(tf.keras.layers.Dense(units=1, activation='sigmoid'))\n",
    "\n",
    "model.summary()\n",
    "\n",
    "## compile:\n",
    "model.compile(optimizer=tf.keras.optimizers.SGD(),\n",
    "              loss=tf.keras.losses.BinaryCrossentropy(),\n",
    "              metrics=[tf.keras.metrics.BinaryAccuracy()])\n",
    "\n",
    "## train:\n",
    "hist = model.fit(x_train, y_train, \n",
    "                 validation_data=(x_valid, y_valid), \n",
    "                 epochs=200, batch_size=2, verbose=0)\n",
    "\n",
    "history = hist.history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(16, 4))\n",
    "ax = fig.add_subplot(1, 3, 1)\n",
    "plt.plot(history['loss'], lw=4)\n",
    "plt.plot(history['val_loss'], lw=4)\n",
    "plt.legend(['Train loss', 'Validation loss'], fontsize=15)\n",
    "ax.set_xlabel('Epochs', size=15)\n",
    "\n",
    "ax = fig.add_subplot(1, 3, 2)\n",
    "plt.plot(history['binary_accuracy'], lw=4)\n",
    "plt.plot(history['val_binary_accuracy'], lw=4)\n",
    "plt.legend(['Train Acc.', 'Validation Acc.'], fontsize=15)\n",
    "ax.set_xlabel('Epochs', size=15)\n",
    "\n",
    "ax = fig.add_subplot(1, 3, 3)\n",
    "plot_decision_regions(X=x_valid, y=y_valid.astype(np.integer),\n",
    "                      clf=model)\n",
    "ax.set_xlabel(r'$x_1$', size=15)\n",
    "ax.xaxis.set_label_coords(1, -0.025)\n",
    "ax.set_ylabel(r'$x_2$', size=15)\n",
    "ax.yaxis.set_label_coords(-0.025, 1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Making model building more flexible with Keras' functional API\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "input_1 (InputLayer)         [(None, 2)]               0         \n",
      "_________________________________________________________________\n",
      "dense_9 (Dense)              (None, 4)                 12        \n",
      "_________________________________________________________________\n",
      "dense_10 (Dense)             (None, 4)                 20        \n",
      "_________________________________________________________________\n",
      "dense_11 (Dense)             (None, 4)                 20        \n",
      "_________________________________________________________________\n",
      "dense_12 (Dense)             (None, 1)                 5         \n",
      "=================================================================\n",
      "Total params: 57\n",
      "Trainable params: 57\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "tf.random.set_seed(1)\n",
    "\n",
    "## input layer:\n",
    "inputs = tf.keras.Input(shape=(2,))\n",
    "\n",
    "## hidden layers\n",
    "h1 = tf.keras.layers.Dense(units=4, activation='relu')(inputs)\n",
    "h2 = tf.keras.layers.Dense(units=4, activation='relu')(h1)\n",
    "h3 = tf.keras.layers.Dense(units=4, activation='relu')(h2)\n",
    "\n",
    "## output:\n",
    "outputs = tf.keras.layers.Dense(units=1, activation='sigmoid')(h3)\n",
    "\n",
    "## construct a model:\n",
    "model = tf.keras.Model(inputs=inputs, outputs=outputs)\n",
    "\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6oAAAEUCAYAAAAiI8syAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+17YcXAAAgAElEQVR4nOzdd3iUVfbA8e+dSW8kIYVACL33LioqghQNgihCdlVEEVQQdW34UxHZtaxYEEEQXRVWEekiHVwUFelSpCMlJEBCGultcn9/TNqkTsgkk4TzeZ485r3vnfc9QUhy5t73HKW1RgghhBBCCCGEqCkM9g5ACCGEEEIIIYQoTBJVIYQQQgghhBA1iiSqQgghhBBCCCFqFElUhRBCCCGEEELUKJKoCiGEEEIIIYSoUSRRFUIIIYQQQghRo0iiKoQQQgghhBCiRpFEVQghhBBCCCFEjSKJqhBCCCHEdUwpdY9SaopSqk2R8cn2ikkIISRRFUIIIYS4Timl3gGeBloCW5RSzxQ6/Yh9ohJCCFBaa3vHIIQQQggh7EApdRjoprXOVkrVB5YB+7TWLyil/tBad7NziEKI65SsqAohhBBCXL8MWutsAK11LDAEaKqU+g/ye6IQwo7kG5AQQgghxPXrklKqe96B1joTGA1ooKPdohJCXPdk668QQgghxHVKKRUMZGutL5dw7kat9Q47hCWEEPZLVP38/HTTpk3tcm8hRM21b9++GK21v73jsBX5XieEKIk9v9cppWYBz2ob/hJ48EKCjkvJtNXlRB1y5uRRbnb6izbNG9s7FFHdHF2hWT91rS93sGUsFdG0aVP27t1rr9sLIWoopdR5e8dgS/K9TghREjt/rwsDmimlwrTWqUVPKqWGaq03VOSCFxPSiIhPs1mAou44uGcXt3RMhphif9VEXefsCc36XfPL5RlVIYQQQojryw2Y29H8opQKyhtUSg1WSu0C1totMlHnpFy5QOMAH3uHIWohSVSFEEIIIa4jWuuzwI1ADLBbKfWIUmoHsAG4Ctxmx/BEHWPMTsXF2dHeYYhaSBJVIYQQQojrjNb6KvAe4AN8BrgAfbXWg7TWv9g1OFGnOKlse4cgaim7PaMqhBBCCCGqn1JqMPAa0Bf4ETgNPIJ5O/AuO4Ym6iAnsuwdQq2XgyLF6IvJwQW45tpEVUhjzE7H3RSHAdsV6pVEVQghAKXUF0AoEK21LtY7UCmlgI+AO4FU4GGt9f7qjVIIIWxiA7ANuFVr/SuAUuoA8IVSqrXW+nW7RifqjJycHBy1JKqVlWL0xdHDGw9lQtXAPFVryNAupCSDpynWZtetNVt/tdYkZ8jWASFElfkKGFLG+aFAq9yPCcC8aohJCCGqwm1a6wF5SSqA1noB5jfrpiilltgvNFGXJMXH0sjHzd5h1HomBxeca2iSCqAUOCtT7oqv7dToFdWLCWmsPhDJ/vPx7A9P4Ibmvnzy9x72DqtWSkxMJDo6mqwseVdL2IejoyMBAQF4eXnZO5QSaa23K6WaljFlOLAot+/gTqWUt1IqSGt9qVoCFOIaZWbn8NGPJzkbk8IDNzThxhZ+FXr9n5FX+eyXM3g4O2BQitiUDBp5uxIel0qnRvUY3685s388xbnYFBp5u3I2JoXENPMby4193fBydeBUVDKmHE2rQA+yTDn8FZ1S7D6tAj0wKEVcSiYP9m2Ch7MDn24/Q9TVdIvrZGbnWMw/GZVE0W6gIfXd8HQpeX5cSiYNvV04cyWFpPSy3wAPqe+Gh7MDp6MLrlOWYB9XPhjd1Zo/VrvSWm8vZXyLUupm4IdqDknUUbFRkfQN9LB3GHWAqrFJah5zfLYNskYnqtFJGby78UT+8b7z8WitUTX9/1QNk5iYSFRUFI0aNcLV1VX+/ES101qTlpZGZGQkQI1NVsvRCLhQ6Dgid0wSVVGjvbvxOJ//ehaAn05cYdMzt9DY17oVjqT0LB7+cg8xyRklnt90JIr3Np8s9fW7z8VZHP9+pvQtYYXnrjt8qdRzZY1d6/yKXKcs8am1/xdyrfURpVQfe8ch6oaU6PM0b17P3mGIWqpGb/1tH+SFs0NBiFGJGVy8mm7HiGqn6OhoGjVqhJubmySpwi6UUri5udGoUSOio6PtHc61KukfT4kVA5RSE5RSe5VSe69cuVLFYQlRuqtpWXyzKzz/ODXTxNc7z1v9+pX7I0tNUkXdpbWWb1zCJlKiw2kS6GvvMIQNbPxlH23ufIKWgyfwzmfLq+WeNXpF1cnBQOfgeuw5F58/tv98PI28Xe0YVe2TlZWFq6v8mQn7c3V1rc3bzyOAxoWOg4GLJU3MfdZrAUDPnj1tV/5O1Hnf7g7n653n6diwHm8M74CT0cC/Nx5n45HLZGSVv/W0qExTDmlZJouxBb+c4fsDJf7VLSY+NbPC9xRCiDw6PQlPd9s+tyiqn8lkYtK/PmXL5zMIDqxPr9HPcXf/3rRvGVKl963RiSpA9xAfy0Q1PJ5hXRraMaLaSVZSRU1Qy/8ergEm5xYZ6QNcledThS2djErilVWHydFw5GIi7s4ONKnvxqfbz9j0PlrD5UT770765/AOtA70ZNfZOD7YUvr2YWs8clMzBncIJCopgynf/mH16+q5OrLgweK1Ly4npvP0kgMWY7e18eeJW1uUeT1XJ6PV9xbieiCtaapf7wdeIeZqWrFxv3qu7P76zWu65u7Dp2gZEkTzxg0AGDO0H9//b5ckqt2b+Fgc7z8fX8pMIYS4dkqpb4HbAD+lVATwOuAIoLWeD6zH3JrmNOb2NOPsE6moE7RGY/nmzeYjl8nJX3/XfPHbWTydrfkxral8AQtbXKPA1KFt2XY8ml1nS37Gs7mfO3/v0wSDQdGlsTdf/naW+FRrfqHVfDmuN89+d4CE3PlODgYm3dac+p7mVZv//n7O4g3urx7uydPfHeRqWvHrP9W/OX1CPMDoRNFKJYt+P8++Qr9zPHFrC/o0r29FjEKIPE5KOnZUt5iraXSY+GGx8SOfPnvN14yMiqVxg4JCfMEN/Nh16EQZr7CNGv2MKphXVP2J5wHjFm40/MmRi4mkF9nGJOo2pVS5Hz/99FOl79OgQQNeffXVSl9n48aNKKU4ffp0pa8lqo/WOkxrHaS1dtRaB2ut/6O1np+bpKLNJmmtW2itO2mt99o7ZlELmbJg+SOk/yuY1W+M4G+f7uDoxUSGz/0tvyjRvYbt7HF+gq1OzxOc+VeZl/uHw1IOOE/gv45v4UVyhcNxIotPHGdx2Hk8Mx3moyh9e3FjFcX3Tq9yyHk8TxpXA2BQEKKiWOP0CoecH+VJ42r6t/Fn3E1NmTnAk42ur3HIeTxftNjOy0Pb4uxgwM/DmQ/uaYFhSRi8FYzLm77sNj7Kjy4v0EGds7hnm0BPlky4gWb1jCxw+oATbo/R//gM3ru3E/VcHfF1MvG/4M+pP6c1rJkCOTm8PbIzjbxdcTTC0iZruG1lD7b5v0+wi+WztjMa7ebRnYPgXwHwYQc4vt58Yu+X8O9mLM58mlu9LuNoVDwuSaoQ10R6qNYNumhpdUDZuMJvSWr2iur5Hfhvnc4ul90Y0Gww9WJHVkf2nIujXyt/e0cnqsnvv/+e/3laWhq33347r776KnfddVf+ePv27St9n/Xr1xMQEFDp6wghRKn2L4Q/V+AC3MNP/HS+PXfOLli1a0gM7zh+hqMy4a8S+chxDoMy3wUUoZ2DeOWudvlzHS/tw2+JOWHsZ/yTHb32kXTrGyXe1tfdCWcHI7HJGWSaCpJRjx3v4rlrNwCjHLYzcFgY6W3vsXit0aDw93BGr34Sw0HzNuQXHZfy4j+mkubZFL1qIm7HzuaPE/o8OBgJOTwX9F+g4PbI+dw+cgJjbxyEk9GAYfencHJDwdeSlUgLEvmh7SYMY9cQm5yBSWsCcldJ/9drN+rXvZAD/PFfBrYcwL5Xh6N3L8Bx09aCP9ugLrTs9Si/vtSfzMOrcV5pbgfqG72T7d1ak3XXLJwdjKRdPonrpw+Azv2zSIyElRPg8V9gw0tgysA5LY6vWq4n/f6lsqVXiGuQmpSIn3vNTjWEdYIb+HHhckz+ccTlGBoGVH2RLKtWVJVSQ5RSJ5RSp5VSU0s4/6FS6kDux0mlVIJNonNwhgu7MOQW1rzNcBBX0vnxWK2tGiquwQ033JD/0atXLwBatGhhMV5au5P0dOufw+revTvBwcE2iVkIIdAaUmJJSM3ElKMhKw3WPWcx5WmHlTiTiQepAPzN4UccVcGuodaGSPoajuJLIuNvbkaQUzpBHo4EeTrht2+2xbU89n9KUD3XEj+cHcyJVn0P54Jxl2w8d31gcQ2fs+uKvTbA0wWlFIaDiy2/vj2f4+powO3YMsvx/YvM/y06/8hKXByNGAwKNr5U4h+Z4ezPEHOK+tnR+UkqWemoX98vcq3VOBgNOB4v0u5z3T8gt42d807LPx/DH4twzkiAmFO4bv2/giQ1T2YSfD8JTAUrr+r01uJJalYaXDlR8BF3hmKNXIUQxEZF0jzQ095hCBvo1bEVp85f5GzEZTIzs1iy4Rfu7l/1XazKTVSVUkZgLjAUaA+EKaUslq+01s9qrbtqrbsCHwMrbRJdw+5Qr6DIpqvK5BbDIbYeiypxCVpc3+bPn49Siv3799OvXz9cXV35+OOP0Vrz3HPP0bFjR9zd3WncuDFjx46laNuQolt/x4wZw80338z69evp0KEDHh4e3HrrrZw4UfE9+cnJyTz55JMEBATg6upKnz592LZtm8Wcn376iRtvvBFPT0/q1atH9+7d+f777/PPr1ixgm7duuHm5oavry99+/Zlx44dFY5FCFENMpLQC26Dmc059c5N/OudNzC906zYtOaGy/zhPJE/nCcy0fgDY4zbis351ulN9rs8TtcvmsK/m8I/68MMXzi1qfh9M1Osi+/4Oni7hDfmLh8qeX5OCY/c7PwEPupSfDz+XMnz06x8D3tOT5jVEb4Yak4Kj64uIc7D5v/GlbA1+tyvEHUULu4vfm5mc/P1T28p+d7nfys+llroOdsjq+G91jC3d8HH7G7maybLm+hCFJYYFU6LwFrZN10U4eBgZM4rExn82HTaDZvE/YNvpkOrqi2kBNZt/e0NnNZanwHIrXg5HDhayvwwzEVIKk8paDfM/MMw11DjbjbF9+bYpSTaN5S//KK40aNHM2nSJGbMmIGvry85OTnExcXx6quvEhQURFRUFDNnzmTQoEHs37+/zEq0p0+f5tVXX2X69Ok4Ojryj3/8g7CwMPbvL+EXoDKMHTuWrVu38vbbb9O0aVPmzZvH4MGD+fXXX+nduzexsbEMGzaM0aNHM2PGDEwmE4cOHSI+3rwl8OjRo4wZM4YXXniBDz74gNTUVPbu3Zt/XghRw+z5HHXJXDW2l+EkvTJLr2rrpswreC87flv5+146CE1uLHuO1rCh2OYos6sRkJEMzh6W44mltLNJKKEna+xf5q20RaWWXFipVOE74Pe5cGJ98XPx5yAz1ZzIFnXoO3C34eNB8WfBzRdycszbgjMSi8+JPQ3b34M737XdfYWo5VKjw2nS2af8icKm/Oq5llg4ya9e5VpV3nlrT+68tWelrlFR1iSqjYALhY4jMLdmKEYp1QRoBvyv8qHlKpKo3mHYhxcp/HvjcRY+0ttmt7meNJ26zt4hAHDunbvKn3QNnn/+eSZOnGgx9uWXX+Z/bjKZ6NGjBy1btmTPnj307l3636O4uDh27dpFkyZNAPNW4rCwMM6dO0fTpk2tiufAgQOsXLmSJUuWMHr0aAAGDx5M27ZtefPNN/n+++85duwYKSkpzJ07F2dn5/w5efbv309AQABvvfVW/ljhZ3SFEPanteavo/tJvnyKrr9Mt08QB76BkL7FKthauHoBroaXfE7nmJNd/zYQuR8cXSC4FxxbY30MV46Zk7aiDi+FIW8DFdgR9dtsyLhaQpwmOLQE0ktYpY3cB242LHwUdxYa9TBv8U2+XPq887LDRYjCMhNj8PMOsncY151rbUFTE1mTqJb00660nzJjgOVa6xLL8iqlJgATAEJCrFwubtwH3AMgxbylxl1lsM/5cRadGcTn/6qHu5cvDu4+KJd6GF29cHT3wcWzPu7e/nh6eePt7oS3mxPuTsba3sNRWKmkBG7NmjW89dZbHDt2jMTEgnfDT548WWai2rp16/wkFQqKNkVERFidqO7evRuj0cjIkSPzx4xGI/fddx8LFizIv4+LiwtjxozhkUce4ZZbbqFevXr58zt37sylS5cYP348Y8aM4cYbb8TNzc2q+wshqseOjx/hpjjbPPlyzf74GpzrwZC3Sp8Tua/sa+yYDae3Qk4l2krsX1h8LCcbPmgHQ96x/jolJal51pbSaiH6KFa12gloDy1uB1cf+N8/S58Xl9vHtuifm5On+bnWwvfNTAUn+d4sBIATmfK7t6gUaxLVCKBxoeNgoJQ9QIwBJpV2Ia31AmABQM+ePa17S9VghO4Pwi8FhRQclYlHHTZANhCX+1GCVO3MFV2PE9QjnnokOfiQ5lSfDBd/st0CwbMBDt5BuPoEUd/LAz8PJ/w9zYUmjAb5h1VbBQYGWhz/9ttv3HPPPYwZM4ZXXnkFf39/srKyuOWWW8ottuTt7W1x7OTkBFSsSNOlS5fw8fHB0dGxWJx5W3cDAgLYtGkTM2bM4N577wVgyJAhfPzxxzRp0oTOnTuzcuVKZs6cyeDBg3F2dua+++5j1qxZ+PpWfdU1IUTZjhw7Yv8kNc/OudDjYfBvXfL5yCKPLhgcIadQC4mTG6ssNLJS4YcpVXf9fOX8itG8PzyU++zr2V/Knhtnrmhc7JnXPhPgyKqCRFabzM/4htxQ8XCFqIOclbSTFJVjTaK6B2illGoGRGJORv9WdJJSqg3gA/xe9Fyl3fIinNwEUX9W6GVuKoMmKpom5BY4yAHScz8K7RbK0YpYPLmifTilvfmfCiLJvQk5Pi1wDmyNd1BTgn09aRnogb+Hs7w7VMMV/f+zYsUKQkJC+Oabb/LHrqUg0rUKCgoiPj6erKwsi2Q1KioKH5+CZzf69evHli1bSElJYcuWLTz77LOMHTs2v0fsiBEjGDFiBAkJCfzwww8888wzGAwGvvrqq2r7WoQQJUi6jGl9yVVsr5mzF/SeAL+UsIXWGptfMa8WluTUZsvjfs/BzxVY5bQXZTAn1aaM8ueWp1GPgs8bdsW8AltKcnthF+ycZ15lLqxhd4g/X5CognnVVRJVIQBwVNJDVVROuYmq1jpbKTUZ2AQYgS+01keUUjOAvVrrvAdXwoAluirK8Tq6wKiFsGg4JEbY/PIGpfEnEX+VSHvOAwchDfPHRcjY78g5HchO3ZizDi246tsJY+NedGzagO4hPgT7uNaq5LWqng2tqdLS0vJXQvMUTlqrWu/evTGZTKxatYr7778fMD8nu2LFCm6++eZi893d3RkxYgR//PEH8+bNK3be29ubBx98kK1bt3L0aGk1zYQQ1SL+HHpuHzpnl73L4kdTN47rxmRqR4JULJ269SEk6wwXL0aCoxttYoskQW6+cNvL4OIFW6YVv2DvCeDZwFy4yL8N/PYRpMYWnD+1uXhCWpquYXB2u7l4UWV5NSq5kJItDHgdgnvCVxX8GdbsVjj7s+VYo+4Fnzt7mv8Mrxwv+fVxf8HGEopPNeoBCeHw5/KCsaKr1TWQUuoLIBSI1lp3LOH8bcD3QO5SMiu11jOqL0JRF2RmpOPlVP48IcpiVRderfV6YH2RsWlFjqfbLqwS+LWEKX+Yt97EnCL1agxJV2NJS4rDlJqAISMRh6wkHLIScc5OwiM7ASds806Os8qijYqgDRGgf4dYyIoxcmR/UzbktOWIQztyGt/EgO5tuKN9IO7O0ty4JrnjjjuYP38+L7zwAkOGDGH79u0sWbKk2u7ftWtXRo4cyYQJE4iLi6NJkybMmzePc+fO5SfMecWWhg8fTnBwMBcuXOCLL77g9tvNKyKzZ8/m0KFD3HHHHQQFBXH8+HFWr17NE088UW1fhxCiBPsXocpJUidlTmFdjuUq2/bb+uNZ3402eQML+ltuLW0/AowOcNPTYHSyTJQCOsCdMy1v0udx+LADpFi23SqXW33wbgK9x9smUZ24HdLize1aKmPgG7C1UAMBozN0exDc68Ok3ea2MNbq8XDxRLVhd8vjRj1KT1RL4hkEXkGWK7NQ/vO/NcNXwBxgURlzftFah1ZPOKIuir0cSfMA6aEqKqd2ZVQOTuYtNSE34AaUWa5Aa3MJ+eRodHIUmVejSY27RObVS5gSL2FIjsIxNQqX9Cu4Z1e8xYejMtFV/UVXw1/AOrLCP2TnuXa8u6oPKS1HMLB7a/q39c9vsi7sZ+TIkfzzn//kk08+4ZNPPqFfv36sXr2aDh06VFsMCxcu5IUXXuC1114jKSmJLl26sHHjRnr16gWYiyllZ2fz0ksvceXKFQICArj77rvzq/x27dqVDRs28MwzzxAfH0/Dhg2ZPHky06dPr7avQQhhSWtNyoHVeJQ1x7MhV137Q3hBG5Xb2vjT2LdIm4Ahb5tXCnOyweBgTsrydAkz12nIS0Jvf5ViHJzhlhdgw4sV+yJ6PZbbCu5uCOwEUYcLzvk0M1fVTbPyZ2STm8Hdz/zR5W9wcHHFYsnT/Da44Uk4tBSij5jH+kw0J6lgXv3seJ/lSqabH3gE5BZSKsS3BbS5E7qPLSjw1DbUnGQW1vMROLAYqysS937M/N8GnUAZzc+ngrmVTWqceUW8htJab1dKNbV3HKJuS4iOoEWgJKp1ySOvfMTan/cS4FuPP9fMqZZ7qqrYqWuNnj176r1799rl3sWYssyNupMuw9ULpF0+ScqlExB7Grekc7hlW9mkPFeqdma16UbWu41g9F2DCO0cZNetwceOHaNdu3Z2u78QhZX391EptU9rXb2NuqpQjfpeJ2zqv7+fo9eGUNoaLhQ/OfpriDkJnUYR59iA7w9Ecj42leb+7gzv0oh6bo7FXxO+01zYp/UgCOpieS72Lzj6vfl5ytKePdXaPOfCLnObmfI07g1th5nfBAbzz8GD35p7pvo0hS5jzGNH10BAW3PCmpVmTmAv/gHBPeDKSXMvVc8g88qla24BuuwMOLgEstPBvy1E7IYGXcyta/J6srp4m2OI3A8B7SDpEpgyoftD5u24SZcLeqJ2ut+8wpwnM9XcnubKCfN1uoaBo7u5BU5CbusdzwbQaRTUC4bMFDiy2hxPp/vApaCqesGf/y44sQ5yTOYtxkmXzf1aLSgI6WNOdo25/w+/GWVe9W7U3bzCGtLX/MZBOez5vS43UV1bxtbfFZiLaV4EntdaHynvmhsOX9IR8SX0tRXXpX3rFvJqXyPBAdJH1RYSnIPxdrPv+uL2vX/i4ebKQ1M/LDVRTUjNxjuj0GOazp7Q4+FrToIkUbVGahxcOUHOpUOknNuLIWIX7sklNDkvIkcr1uX04cfAcTw6Yiidgkv4wVgNJFEVNYkkqqIuyMzO4aZ3fuSnrL/jriyL+6Q3G4DL2BpSAVjUWDU4UfUCcrTWyUqpO4GPtNatSrlOftvBp6a926PTgHurLmhRq/z633/zxUPtMRoN9g6lTriWRDUmPpGJr81iwb+eob63l03iOBcZRegT/6y2RFX+9ljDzRea9MVww0Q8x3yG+/OH4LmTMGohuvdE0r1blvgyg9IMM+7k/SuPs33+ZKZ+t4crSTaoViiEEMKu/vfHCV7KmF0sSQVw7lcd7VeEqBpa60StdXLu5+sBR6WUXylzF2ite2qtew6974FqjVPUbE46S5JUO1u0chPxkadZuGKTvUO5ZvI36Fp5BkKHEag738XlmX0waQ85t04l061BsalGpZnksIaxR8bx9KyF/HKqgsUuhBBC1CgBW6dwn3F7sfEJ9eajmt9W3eEIYTNKqQYq93klpVRvzL8rxpb9KiEs2aqgqbg2MfGJrN2yjXkjA1m7ZRuxCYn2DumaSKJqK/6tMfR/GafnjsCohWTUL761sZ3hAguzp/Lbwtd4f9NxcnLss+1aCCFEJVz+k+4Zu4sNrzP1plu3ClSjFcIOlFLfYu5530YpFaGUelQp9bhS6vHcKfcBfyqlDgKzgTFV0npQ1GlO0kPVrhat3ERoC0WbQBdCW6hau6oqiaqtGR2gwwicJ+0wJ6yugRanHZWJqQ7fore/x4srDmGSZFUIIWo+reHXD+HLu2D+TSVOiXMK5m99Qqo5MCEqRmsdprUO0lo7aq2Dtdb/0VrP11rPzz0/R2vdQWvdRWt9g9baBn2LxPUkOzsLV4MVBd1ElchbTX2oh/m51Id6eNXaVVVJVKuKwWBOWKfsIqfT6GKnn3dchsuBL3lz3TE7BCeEEKJCTqyHrdPh/K+lTgkbdCP1XEuo5iuEENeRhCtRhPi72zuM61beaqqfh7n4kp+Hg01WVcOen0nfsBc5cS6S4P7j+M+KzbYIt0y1q49qbeTqg+HeBdD+brJXPo5DVlL+qRkOX/Hk7/X4IWQiw7o0tGOQQgghynR8XblTHBr3qoZAhBCiZouLiqBnQFkdpkVV+mn3QS5eymDx4UsW4w1jDvKPR0dd83W/fe+FyoZWYZKoVpd2oTg8uJycRcMxZKcD5qrA7zp+yr0rWtAu6B5aBkhjZCGEqJHO/1b2+e5jzT1OhRDiOpcaHU6zztI/1V7WfPove4dgM7L1tzqF3IBh9DdoVfD+gJdK410+4slFu0jOyLZjcEIIpdQQpdQJpdRppdTUEs43UUr9qJQ6pJT6SSkVbI84hR2UUkumV/onTG25Bu6eXc0BCSFEzZQSc4HGAd72DkPUAZKoVrdWA1FD3rIY6mY4zYiEhUxdcQgprCeEfSiljMBcYCjQHghTSrUvMu09YJHWujMwA3i7eqMUdpGdCVcvFBteZbqJK3jj4lVii0khhLguOWSn4ewkz+vbli7t/dIawxyfbYOURNUeek9Atx5iMfS48QfCD//KmoMX7RRUzRUaGkqnTp1KPT958mR8fHzIyMiw6nqnT59GKcXGjRvzx4KDg5k6tdgCmoUDBw6glOLXX0svplKS+fPns2bNmmLj1tzTVrKzs86T0XQAACAASURBVFFKMX/+/Gq5Xy3VGzittT6jtc4ElgDDi8xpD/yY+/m2Es6LuujqBdCWFSx357RhRtaDAPh5ONkjKiGEqJGclOwQtDVjdjoZ2lhjk1WtIUMbMeY+3mgr8oyqPSiFGv4Jet5NqGTzg84GpXnL8T88trYNt7cNwNNF3onKExYWxgMPPMCRI0fo0KGDxTmTycTy5csZOXIkzs7O13yPH374AT+/qlkVmT9/Pj179uTuu++utnuKa9IIKLxsFgH0KTLnIHAv8BFwD+CplKqvtY6tnhCFXcSdsTg849aZ++MK3mTydb/27z1CCFHXOCE9VG3N3RRHSjKkO7gAyt7hlEBjzE7C3RRn06tKomov7vVRI+bC1yPzhzoazjEk7Qc+2tqYV0OL7ji8fg0fPhw3NzeWLFnCP//5T4tz27ZtIyoqirCwsErdo1u3bpV6fW25pyhTSd/5i753+TwwRyn1MLAdiASKvXWslJoATAAICZG+mrVekUQ10mBZpb2+rKgKIQQAOTk5OBX/sSgqyYDG0xQLJntHUr1k6689tRwAHe+1GHrOYRkbduzj+OXa15S3qnh4eBAaGsp3331X7NySJUsIDAykf//+AERGRjJu3DiaNWuGq6srrVu35vXXXycrq+x390rahvvxxx/TuHFj3N3dGT58OJcvXy72upkzZ9KzZ0+8vLwIDAxk+PDh/PXXX/nnb775Zg4ePMh//vMflFIopfj6669LveeSJUvo2LEjzs7OhISEMG3aNEymgu9Kn3/+OUopjhw5wsCBA3F3d6ddu3Z8//335fwplmz27Nm0bNkSZ2dnWrVqxezZlgVhwsPDue+++/D398fV1ZWWLVsyffr0/POHDx9m8ODB+Pj44OHhQfv27Wvz9uIIoHGh42DAYi++1vqi1nqk1rob8Eru2NWiF9JaL9Ba99Ra9/T396/KmEV1iDtrcXhWB1oc13eXRFUIIQCS4mNp6O1q7zBEHSErqvY2+G30qS2oDHNi6qHSmWr8mmmrW/LdxBtQqgqW96fXs/01r8X0Yr/flyosLIylS5eyb98+evToAUBWVharVq3i73//O0ajEYArV67g5+fHrFmz8Pb25vjx47zxxhvExMQwd+5cq++3YsUKpkyZwqRJkxg2bBjbtm3jscceKzYvIiKCKVOmEBISwtWrV5k3bx4333wzJ0+exNPTkwULFjBixAjatWvHyy+/DEDLli1LvOf69esJCwtj3LhxvPfeexw4cIBp06YRFxfHnDlziv15TJgwgRdffJFZs2YxevRozp49S1BQkNVf47x583jmmWd47rnnuOOOO/jxxx955plnyMzM5PnnnwfggQcewGQy8fnnn+Pl5cWZM2c4deoUAFprQkND6dKlC4sXL8bJyYnjx4+TmFhr32TZA7RSSjXDvFI6Bvhb4QlKKT8gTmudA7wMfFHtUYrqF2+ZqJ7Osnzzob6HbP0VQgiA2KhIbmwg7RaFbUiiam+egaiBr8O65/KHhhl38k34r6w+0Jh7ukn3C4ChQ4fi7e3NkiVL8hPVTZs2ERcXZ7Htt2vXrnTtWtDL8KabbsLV1ZXHH3+cjz76CAcH6/7Kv/nmm4SGhuYniIMHDyYqKoqvvvrKYt5HH32U/7nJZOKOO+7A39+fH374gb/97W+0b98eNzc3/P39ueGGG8q857Rp0xg4cCBffGHOfYYMGUJOTg7Tpk3jlVdesUhCn3/+eR566KH8r7lBgwasW7eO8ePHW/X1ZWdn88Ybb/Doo48yc+ZMAAYNGkR8fDxvvvkmU6ZMwcnJid27d7Nq1SqGDh0KkL9yDRAVFUV4eDgbN26kXbt2AAwYMMCq+9dEWutspdRkYBNgBL7QWh9RSs0A9mqt1wC3AW8rpTTmrb+T7BawqD6JkRaHh5K8LI59ZUVVCCEASIk+T/PmNWRBRNR6svW3JugxDh3UxWLodYeF/HvdEVIzZZ8/gLOzM/fccw9Lly7Nb+Hz3Xff0aRJE4sEMCcnh/fff5927drh6uqKo6MjY8eOJS0tjYiICKvulZmZycGDBxk+3LKg68iRI4vN3bFjBwMHDqR+/fo4ODjg7u5OamoqJ0+erNDXl5WVxYEDBxg1apTF+OjRozGZTOzcudNifNCgQfmfBwQE4OfnZ/XXB+YtvVFRUSXeLyEhgSNHjgDmJPill15i4cKFXLhg2Z7D39+fRo0aMXHiRJYuXUp0dLTV96+ptNbrtdattdYttNZv5o5Ny01S0Vov11q3yp0zXmttXalpUbslXrI4vKwLGtk7GhVeLvKerxBCAKREhxMS6FP+RCGsYFWiqpQaopQ6oZQ6rZQqsZ+GUup+pdRRpdQRpdRi24ZZxxmMqDvfsxhqZ7jA4LR1fP7L2VJedP0JCwsjPDyc33//nfT0dL7//nvCwsIstke///77vPTSS4waNYo1a9awe/fu/Ocu09OtK5kdHR1NTk4OAQEBFuNFj8+ePcvgwYMxGo0sWLCA3377jT179uDr62v1vQrf02QyERho+exb3nFcnGUVNW9vy0baTk5OFbrnpUuXLK5f2v2WL19O165defrppwkJCaF79+5s27YNAKPRyObNm/Hz82PcuHEEBQVxyy23cPDgQavjEKLGy86A1Jj8Q5NWXKHg3199d+eqeURDCCFqIZ2ehKe7i73DEHVEuW8DK6WMwFzgDszFRvYopdZorY8WmtMK8/NaN2mt45VSASVfTZSqcW/oEgYHv80f+ofDMu76+WbCeofg72nDZ6Aq8GxoTXL77bcTGBjIkiVLuHTpEklJScWq/S5btowxY8YwY8aM/LFDhw5V6D4BAQEYDIZiK4RFjzds2EBGRgarV6/G1dVcOCAzM5OEhIQK3S/vnkajsdg9oqKiAPD19a3wNcuSt424vPsFBwezaNEiTCYTu3fvZtq0adx9991cuHABb29v2rdvz8qVK8nMzOSXX37hxRdfJDQ0lPDwcPnlXdQNSZZF1GKohwlj/nH/tvLjTggh8khrGmFL1qyo9gZOa63PaK0zgSUUb3L/GDBXax0PoLWu/XsA7WHgdLSTR/5hPZXKkzmLmf3jKfvFVIMYjUZGjRrFsmXLWLx4Me3ataNz584Wc9LS0or1U/3mm28qdB8nJyc6d+5crJLuypUri93LaDRaPPe6ZMkScnJyil2vvNVOR0dHunXrxrJlyyzGly5ditFoLPf51opq0qQJgYGBJd7Px8enWL9ao9FI3759mTZtGsnJyYSHh1ucd3JyYsCAATzzzDNERETU5oJKQlhKKrrtt+BNowm3NGf63dJKTAgh8jgpeWRN2I41D9Y0Ago/nBYB9CkypzWAUuo3zEVIpmutN9okwuuJZwPUrS/Bltfyh8YYf+KuPb9x5qamNPf3KOPF14ewsDDmzJnDqlWrLFZN89xxxx3MmzePnj170rx5cxYtWsS5c+cqfJ//+7//4/7772fy5MncfffdbNu2ja1bt1rMGTBgAC+++CLjxo1j3LhxHD58mA8//BAvL8tCK23btmXbtm1s3rwZX19fmjdvXuIK6RtvvMFdd93F+PHjGTVqFAcPHmT69Ok8/vjjFarmaw2j0cjrr7/OpEmT8PHxYcCAAWzbto3PPvuMd999FycnJ2JjYxk2bBgPPvggrVu3Ji0tjffee4+GDRvSpk0b9u/fz8svv8zo0aNp1qwZcXFxzJw5kx49elCvnhRSEHVEokWHIqJzn08d0bUh/3dnO3tEJIQQNZLWGkctK6rCdqxZUS1p/54ucuwAtMJcETMM+Fwp5V30RUqpCUqpvUqpvVeuXKlorNeHPo+j67fKPzQozRTDMmZuOmHHoGqOvn370rRpU7TWjBkzptj5N954g/vvv5//+7//IywsDHd3dz788MMK32fUqFHMmjWLVatWMWLECA4fPsxnn31mMadr16785z//YceOHYSGhrJ06VJWrFiBp6dlWfZp06bRunVrRo0aRa9evVi/fn2J97zzzjtZvHgxO3fuZNiwYcyePZsXX3zRorKwLT3xxBN8+OGHLF++nNDQUJYtW8aHH36Y35rGzc2N9u3bM2vWLIYNG8a4cePw8vJi8+bNODs707BhQ/z9/fnXv/7F0KFDmTx5Mp06dWL16tVVEq8Q1S0qMZ2tuw9YjOUVUhraybZvHgkhRG2XlpyEn4ejvcMQdYjKq6Ba6gSl+mJeIR2ce/wygNb67UJz5gM7tdZf5R7/CEzVWu8p7bo9e/bUe/furfQXUCcdWwvf/d1iKDTjX7zx+AP0aFLxSmrHjh3Lbx8ihL2V9/dRKbVPa92zGkOqUvK9rnbSWjPwg58ZHb+ACQ7r8sdnZt3PXNMIdv3fAAK9pGCIuHZ17XvdhsOXdER8mr3DEHZ04dRROkav5f5bO5Q/WVwfnD2hx8PXXLTEmhXVPUArpVQzpZQTMAZYU2TOaqA/gFLKD/NW4DPXGtR1r+1d6IbdLIaec1jG2+uPUd4bC0IIISovPC6Vv66kEKjiLcaj8KGBl4skqUIIUURiVDgtAj3LnyiElcpNVLXW2cBkYBNwDFiqtT6ilJqhlLo7d9omIFYpdRTYBrygtY6tqqDrPKVQt79qMdTfeBAdvpPNR6PsFJQQQlw/ktLNBUEaKMvWUJe1L52D5RlsUbsppb5QSkUrpf4s5bxSSs3ObUt4SCnVvbpjFLVPypVwmjSwbZcCcX2zqo+q1np9boP7FlrrN3PHpmmt1+R+rrXW/9Bat9dad9JaL6nKoK8LLQZASF+LoamO3/Lv9cfIMuWU8iIhhBC2kJhuLggSSJEVVe1Dl8bFSjAIUdt8BQwp4/xQzLVHWgETgHnVEJOo5bISY6lfz93eYZQoJiGZe6fOJ/Zqir1DERVgVaIq7EApuP01i6FehpO0iv+Z7/ZcKOVFQgghbCEpPRsDOQQpy81Bl7Uv3SRRFbWc1no7EFfGlOHAotyFiJ2At1JKKoiJMjmRWWN7qC9at4P4yxdYuPY3e4ciKsCa9jTCXpreBK2HwMmCTj/POiznwS19GdGtER7O1v/v01rX2G8e4vohz1iL2iIpPZsgYnEu1BMwVnvi5uVDr2aytU3UeSW1JmwEWDQWVkpNwLziylPT3qXTgHurLcCa5O3JYSQnJxUb9/Dw5OU539ohomtT2a/DWZmqIqxKi0lIZu3Pe5g30o8n1u5hbOhNNXblV1iSRLWmG/gG+tRmlDZv921ruEC3tN/5bHsznr2jtVWXcHR0JC0tDTc3t6qMVIhypaWl4egopetFzZeYlkUTg2VNgHAdSFjvEByNshlJ1HnWtCZEa70AWADXd9Xf5OQkmo//uNj4mc+fskM01y7v67h84QwmU0HSeWHJq7zycGi5Caujqpk9VBet20FoSwNtApwJbZnOwrW/8Y+/D7J3WMIK8tO2pgtoi+ow0mLoKYdVfP7LaaIT0627REAAkZGRpKamyoqWsAutNampqURGRhIQEGDvcIQoV1J6Nk1UkUSVQP7WO8ROEQlRrSKAxoWOg4GLdopFVDOTyYSzX0j+h6OHL83Hf1ziamuejPQ0vJyqMUgr5a2mPtTdvIL6UHd31v68R55VrSVkRbU26Pcc/Lk8/7CT4Ry3Zf7OrB8b89Y9ncp9uZeXFwAXL14kK6tmvtsl6j5HR0cCAwPz/z4KUZMlpWcVS1Rbt+1CgLSlEdeHNcBkpdQSoA9wVWt9qZzXCLBYjYyPieaVh0OB2rcNuKLioi7SPKDmtabJW0318zCnPH4eDoS2NJS5qhqTkMzEd75mwcsPyhZhO5NEtTYIbA/th8PR7/OHXnD4jsF7evHITU1pacU3Bi8vL0kQhBDCSonpWfQskqi269DFTtEIYVtKqW+B2wA/pVQE8DrgCKC1ng+sB+4ETgOpwDj7RFr75K1GAvkrkVAztwEXfSY1PiaayHOnMGVXfFEjITqiRvZQ/Wn/SS5GZ7D4cLTFeMOok6UmqoULL8kWYfuSRLW2uH0a+thalDa/S9fUEMUo9T/+vbEhnz3U087BCSFE3VLS1l98m9snGCFsTGsdVs55DUyqpnCEnRR9tvbQnCdw9gsh9fKZCl8rLfocTfr62DI8m1jz/uQKzZfCSzWLJKq1hV9LVI+xsPeL/KGnHVZw69F+7DnXnF5NpQqlEELYSmJapiSqQgireHh45q+YxsdE4+hh/p3M6FK7ilgaXdy4+NUzZCRewdnL32K8PGlxlwmq374qw8tXlVtzrSm8JFuDq48UU6pNbn0J7VjwzcJfJfKgcQtvrT8mRZKEEMKGvFPO4KYy8o9Njh7gVt+OEQkhaqqX53zLm1+t5c2v1uLjF0DnyfPoPHkeHca/b+/QKqTD+PfpPHkeDkZHPFwc8j9cyeTM50/h4VH61l5HnYmxmiqiV1VPVGsKL8UkJDPoqVlER4ZLT9ZqICuqtYlnA9QNT8Iv7+UPjXdYx1fhg9n452WGdpJe3EIIYQsDU9ZaHGcEdMFNelELIa4D9er78eZXa8ufWIhToZ7TVamqtubGJCQzaMoswtoXFF6q52Kgh08yn6zYxmuPmItizVvxEyotjpvberL2Z9kaXNUkUa1t+k6CXfMhMxkwr6o+YNzCvzd6M7B9oPT3E0KIyspIYlDW/yyGsro8aKdghBC1SeFtwEXH7a2k4kmH5jyB0cWt0qu/Trp6ukpUVU/URet2cCUmls92O/PdkUwAElPSSUtLp37kfl57JJSYhGRWbPmdOXe6Mm1bKv3bOEnBpSomiWpt4+YLvR6F3z7KH3raYRWrYvvx7e5wHurb1H6xCVHLKaWGAB8BRuBzrfU7Rc6HAAsB79w5U7XW66s9UFG1/vof7hT0qb6i6+HRaYQdAxJC1BY1uQVN0eJJea10Li951SK5rmhSnZ2dhavRZLM4S5O3mrr0fnN8D3V35/6llV/VzLvu1sdDeGJtKstmPoPWmvtf/Ih5oYE8sTaV2KspzFvxEwMaZ9En2I3QVjmkmLJkVbWKSaJaG/V9CvZ+CRmJAHipVN5w/IrXNvtyV6cg6ns42zc+IWohpZQRmAvcgbnZ/R6l1Bqt9dFC014Flmqt5yml2mNu4dC02oMVVefiAfT6lyi8yXdtTl8edpH+qUKI2u/I589hSk8tNl6ZPq8JVy7T1N/jml5bkcJE19IT1Zr7lrRKC1iMzV22jZVbf+ebu51wNCge6uLE/ctT6N/GW1ZVq5AkqrWRhz/c8gJseS1/aJhxJwcy1/CvdYF8OLqrHYMTotbqDZzWWp8ByG10PxwonKhqIK8hcT3gYrVGKKrWsbXw3d8p+iTqCYe2KHk+VQhRB5jSU2n48CyLsYyYcJK3zr7ma8ZdjqBX4LUlqhXpWXotPVHLu+8ny7exbddBi1XaEYt3YTQoVozxyh/r9+kO7mqWg1IOHL1i3ubcJRC+3JtIx/iK319YRxLV2qrP43DwW4gu+B36Hw7LuOmPfvzSvRH9WvmX8WIhRAkaARcKHUcAfYrMmQ5sVko9BbgDA6snNFEtdn5S4vA5l7bVHIgQQlRM0edP81RmpdRaqVfCada54j1UK1oYqSI9UctaqS1833v/+xsGnY1S5qTUz8MBf8d0OgUaLVZunclkzWkHfrpUOHVyoGMLvwr3ahXWk0S1tnJwgtFfoz/rj0q/CoC7ymCscTOvrg5k0zO34OJotHOQQtQqJS2ZFe37FAZ8pbV+XynVF/ivUqqj1jrH4kJKTQAmAISEhFRJsMLGTNlwvnirgQTtTrJrIzsEJIQQ1os4ewoHT79i4wlXTlX5vVNiImgc2LLCr6uqwkh51y5tpbbwfYNcMolJzaHXxxH4eroCEBmTzr5IWH+2YOXWwcWDtgGSlFY3SVRrs/otUP2egy3T8ocedtjEl7FDmP3jKV4cIqsAQlRABNC40HEwxbf2PgoMAdBa/66UcgH8AIt9SFrrBcACgJ49e0qT49og5kSJw7HaC08Xp2oORgghKkYrQ7EtvQDn5zyU/7mHhyfxMX+RERNuMcdorNzChkN2Gk6OFUspChdGiknOZtvJqyQc32WTwkRlrdQWvW9mjuKtga68s8+Nle8/K0WRahjpZVLb9RgHLvXyD31UMlMcVrJg+xmOX060Y2BC1Dp7gFZKqWZKKSdgDLCmyJxwYACAUqod4AJcqdYoRdWI3F/i8A85ffHzlAJ1Qoja7+U53+LjF0Cjpq0sPho0bl6p615LD9XChZEW7b1KSnoWXiqNOyZ/SOzVlErFY7lSa8gvjlTSfYe3caRbkAO3Nsy0mCdqBklUazsXL+hruQ1hrHEzTXQE/7fyMDk5spgjhDW01tnAZGATcAxzdd8jSqkZSqm7c6c9BzymlDoIfAs8rLWWf2S1XfRxWFN8O1eiduWb7AHc1yPYDkEJIYTt5fV5LfpRmT6vTlS8h+pP+0+y+HAGXWdfZs5v8Tx3oxNHLqeSkxpXqYQxb8X0oe7mldGHuruz9uc9+clv0fv2CVbEpeVwV0ss5omawap1eit6Cz4MzAQic4fmaK0/t2Gcoix9J8P+RXDVXAfGUZmY5vBfxoa/xDe7w3nwhiZ2DlCI2iG3J+r6ImPTCn1+FLipuuMSVSgzFb65r9jwt9n9+Xf2GD4ZP5AbWxZ/7ksIIWypuooh2bqwUk5ODk5UfEU171nPD77ZDJH7GNTZk3vPhuPk7Fqp3qTltbApet+b2hfsSgy9fFVazdQw5SaqVvYWBPhOay1PGNuDkxsM+icsezh/6FbjIQaY9vPuBkcGtQ8k0Et6AAohRDF/rsh/ky9PljbybvZo3L0DJEkVQlSL5OQkmo//uNj4mc+fsur1BmUo9uxp3rgtlJZIu7q4MOXODmW+trQKvIWfF429mswj3Zx4akMq/ds4XXPCaG0LG1u2uhFVx5oVVWt6Cwp7az8CmvaDc7/kD73m8DWDMjozfc0R5j3Qw47BCSFEDaQ1CT/PxbvI8DzTMOLxom/jeiW+TAgh7Km0pDHq2//D27+BxVijJs0qdI3SVnBLS6T/+mwyl69mlBlvaRV481Y/67kYOBOTQms/B0JbmUgxZV3zqqq1VXmlem/tYE2iak1vQYB7lVK3ACeBZ7XWF4pOkJYNVUgpGPIOfNoPcjtlNDVE8ZhxHXP/HMHWo1EMbB9o5yCFEKLmuHR8F0FXj1mMjcl8lZ057QHoElw0hRVCCPsra/X1za/WVvoaFaGUIiG79MroZVXgzVvVnL/zKmRn4uVi7hLX0EsT2tpZtuEKq4opWdNb8Aegqda6M7AVWFjShbTWC7TWPbXWPf39/SsWqShfg47Q8xGLoSkOK2mlIpj2/Z+kZFT8GQIhhKirIg9utTj+n6lrfpIK0FkSVSGEKJf2DOJKfPHVWSi7Au+a9yez97/TadssGK96XuDsCc6eXMxwYfHhDH7af7K6vgRRQ1mzolpub0GtdWyhw8+Af1c+NHFN+r8Cf66EtDgAnFU27znOZ+TVN3h/80mmDWtfzgWEEOL64BJ9wOL415xO+Z8rBZ2CZeuvEEKUp2GXW9l64AfC+ne0GD9xPooPFm/hfxMbAuYKvPcvLb6lV7bhitJYs6Jabm9BpVRQocO7Mbd2EPbg5gt3zrQY6mI4w0TjWr7acZbDEVftFJgQQtQsAUmWpRYO5hT0EmwV4IGHc8Ua2AtRWyilhiilTiilTiulppZw/mGl1BWl1IHcj/H2iPN6UhVtY6pLoxZt2f1XXLHxqXOX09jDxNqjyYBlBV4hrFHuT2GtdbZSKq+3oBH4Iq+3ILBXa70GmJLbZzAbiAMersKYRXk63gtHv4djBe8nPOOwnK2Z3Zm68hDfT7oJB6O00BVC1HHZmZAYAa4+5o9cmdk5ZCdfISArsmCqNnBEN80/lm2/oq6Sbg41U14Bo7wiRwlXLqOVgfiYaJ4M7Y1BGahX369KE9cjnz9Hekw0rzwcajHu4eGZn0gX5eHhicFgIAlXi/GYhGSOnjzHB4OceWpDPIsOZeX/7imVdYW1rHq72Iregi8DL9s2NHHNlIK7PoDzv0GqeVe2kzKZtwBffIPPfz3L47e2sHOQQghRhU5tgeWPQEYiKCP0ehTunMm2E9G8t3g969TTFtNP6sak45x/3KWxJKqizpJuDjVYXpGjQ3OeoOHDs/LHM2LCadS0Vf4qa2lJo7VKukZ6TDSN/v42DRo3txi3pkiTsX4TLkTF0zjQ/KbgonU7mHijL3d1r8eJ5KvQqIckp6LCZF9TXeXhD3e+B8vH5Q91NpxlonEtH2x24va2AbQOrPnbSYQQosKyM2D1k+YkFUCbYPcCMjvcxwvLkvgw5zPz/qBCDuRY/mLWVVZURd1ls24Owj5Kah9ji2u88nBosSTVWsFdbmXT/sWMH+pj0R8VSn82tbT+qrZWXfcRtif7P+uyjiOh/XCLoacdVtAs5xzTvv8TrYsWbxZCiDrg6BpIiS42vGXdCrqn/ko/45/Fzm3O6Zn/eSNvV9oGyRt5os6yWTcHpdQEpdRepdTeDcu/tnGYojYJbNyMQxHmyr95lX79PMzrYaU9m1q4v2pVqq77CNuTRLWuu+sDcPPLP3RSJt53nM/eM9H8cirGjoEJIUQV2fNZicN3RX/KAqcPi42/kzWG+Ia3MbhDIDe1rM/ssG44ynP8ou6yqpuD1joj9/AzoEdJFyrcdnDofQ9USbCidlBKkYQrWmt+2n+SxYcz6Dk3Ov+jaLuZwv1V1/68h9irKVUSV3XdR1QN2fpb17n7wV3vw7Kx+UMdDed4wriG6T/UY/Wkm/BycbRjgEIIYUOJF+HCLqunT8mczJqcG5nYoj4vD21XhYEJUWPkd3MAIjF3c/hb4QlKqSCt9aXcQ+nmIKzi1qgdpy5csardjGV/1XQWrv2tSp5hra77iKohier1oMMIOHoPHFmVP/SUwyq2xPTk6W/d+OLhXihV0k4gIYSoZSL2Wj31bE4gG3J6A9CvGLYdNgAAIABJREFUpX9VRSREjSLdHGq2vCJH2UkxnJ/zUP64QRnIqOKqv5Ut0hTStR8bd39G65CAMudZ+wxrZZ04H8Wny7fw8xPBFbqPPNNac0iier2483049yukXAHMW4DnOn7EyBNvsOHPxtzZKaicCwghRC0Quc+qaSkOPszzf4dbnBsytFMQN7fyK/9FQtQR0s2h5rJFoSR73ds3oCGHYtLLnVfWM6y2XO2cOnc5oS2ArDTA0er7FH6mVVZf7UsS1euFe33z86pLH8wfamG4xAKnD5i63pv+bQJwdTKWcQEhhKgFLu63OEzQ7nirIs8keQXj/vRB3jXKj0AhhLClJNzIycnBYCj9Of+f9p/kYnQGiw9bFr2zZX/VmIRk9h45yxkXzdKjUfj7pGEwqHLvU/iZ1ifWVmyVV1ZibU9+Sl9P2t8NXcLgYME7Zn0Mx3k06VOe/c6PT/7ePf8fsRBC1ConN5l3jZzdbjE8Nesx5jp+hFEVKmp66wsgSaoQQticV9POHP7rEl1aNSp1jjXPsFbWonU7ePbW+vzjlnp8sN36Pq6VeaZVVmJtT8oaXm+GfQRNbrYYesDhR7yPL+bfG4/bKSghhKiE/f+FxffDjtkWwwnanY05vRiV+ToJXR6DXuNh1ELoPraUCwkhhKiMpl1vZsOBklvuxiQkc+/U+VVeeTdvVfSh7uZVzYe6u1tV8fdaX1f4tVJd2LbkLeXrjYMzjP4vOQtuw5BwPn94hsOXjPklmBWBntzbI9iOAQohRAWYsuGnt0s8dTCnBaDIbtQL73uerd64hBCiDG9PDiM5OanYuIeHp12fU60sT+/6HLiaU+K56lpxvNZnYCvz7KxUF64akqhej9x8MYxZTM7nAzFkpwHm4krznWbxwNogBrQbibebk52DFEKIcsSdhUV3Q2Jkiac/NYUCEODpUp1RCSFEuZKTk2g+/uNi4yVV3a1tUpQHWdn/z96dh0dVnQ8c/56ZyZ6QlSwEQgIJyr5FBJeKsgiCoKgoigiVolZqrVrr9kPq0lqtrVasSl0pyCZFEaKoLG7sssimgOw72VeSzMz5/THZJpkkQzJLlvfzPPMk99xz731jaTLvnHPeY8HHVFn7pDFrPy9UQ9fAOnOdo3WoFT/bqEBueu8Yfx0Vzb1u/hlbC0lUW6vYHhhufAMWT65oilbZvGL5C39f1oFnb71MtqwRrY5SagTwKrYtG97WWr9Q7fw/gavLDgOBaK11mGejFACYi2HezZB9tMapDSkPM2NXNPt0BwBiQ/08HZ0QQrRa4Sn92fTTfi7vkVjR5mjEcdKoy9xSfKiha2Cd3f+1+qhw+c+2Ym8+WQUlLN+Tz+hkk4yquoAkqq1Z9xvh1A747p8VTd0MRxi1+xH+8dmbPHxdby8GJ4RnKaWMwOvAMOA4sFkptUxrvae8j9b6D1X6/w7o6/FAhc2eTyDjQM32e79j1Q9G9ulDFU2xbWREVQjRfDT3acFJvQfx1fK1FYlqbfumFpwvaVbFh2obFV67dR9HTxWRm5fPayP9+N1nWbQJCSbBhVWMWytJVFu7a/4Py+k9GA+srGgaZNxD5vpH2NptPv0SZW9B0WoMAA5orQ8CKKUWAGOBPbX0nwA87aHYRHWb/lOzrd9dENuT07nb7JpjJFEVQjQjTWlacEOS5oCgEPYWVs7Kc7T2c2QnePfzdXx8Z9tGTQW+kC1hGrt9TG3rUJe9PJ1/zPsCTvzAqH6h/JzvfJVhUTdJVFs7gxHj+PcpemcUAWcq9x8cZdzEigW/x/roXNmyRrQW8UDVUoXHgUsddVRKdQSSgNUeiEtUd2YPHN9k3zbubeh5s+10rv2G87GhkqgKIURDOJs0V09oi7LO8tmadUSHBhAbqGus/cwtOE+g0dzo4kMXUqCpMcWcahsVvmv05Witaz0na1QbRxJVAb6BBNy1hMI3hxKY+0tF86jzy/l82TxG3DDRi8EJ4TGOPpHRDtoAbgM+0lpbHN5IqWnANICEhATXRCcqHfne/jjpKuh1S8VhjURVRlSFEB5wIaOPwcEhDkdIg4NDHN6jqaue0Ob+8gNtVBFnV7/Ppjcesuubnp3P+EdfbXRidyEFmhpbzKmuisBAg6sFi7pJoipsAiMI/PUnZL02mHBLekVz1NZ/sWfAGLq1a+PF4ITwiONAhyrH7YGTtfS9Dbi/thtprWcDswFSU1NrS3ZFQ534wf44eUjFt29/e5AjGYV2p2NkRFUI4QEXMmW3rrWmT04e7ZJ4XL3WdffbD2M5b/v9WpqfWRFncHBIzWck9CDz+w8d3qcx28A4uo8zo7KN3T6mrorAQIOqDIv6SaIqKoV1oPTmObDwuoqmVMPPzFjwAU8/OB2jTAEWLdtmIEUplQScwJaM3l69k1LqIiAcWO/Z8ESF6olqu34AbDqUyXMr9tqdCvQ1EuInf+qEEK2Pq9e6Ws4X0m7yKwAUpx8lPjGl1vsZfPwoLS11OFWpodvHVFXXVNzqI6UX0rc2Da0kLBrHqb/e9W3ZUKXfzcBi4BKt9RaXRSk8Jrrr5ZyNvoLos99VtE3P+TsffnUJdw4f6MXIhHAvrbVZKTUdWIntd927WuvdSqlngC1a62VlXScAC7TWMlLqQSVmK3nnS1HFuUSk76to1ygyQ7tBfjFvf3uwxnVdYkJkqy0hRLNS17TgZsUvGKvVWqPZFUnfG0vW0j88n7CAUKDuUVlXjeAKz6s3UXVmy4ayfiHAA8BGdwQqPCd69Ax4t/L/uNEqm+7fTWdr8nL6dYr1YmRCuJfWOg1Iq9Y2o9rxTE/GJGDexiP8Ne0n2hSfZp3/A3bn9lvbMfzFDbVe++Soru4OTwghXKopbUFTNWkuzc+kON22d7XRaKz32qDE3qRvX+6WuJas2UpGRhGf7D9Om6DK5R2ORmVdMYJbm8ZWEhZ1c2ZE1dktG54FXgQecWmEwvMSLqXg0gcJ2vhKRVM/w34Wz/097X7/gVTQFEJ4zInsImZ8shuLVfOqz3s1zu+wdnZ4XbtQf75/7BoZTRVCiEaomjQ/OXl0xXTf08cOcuLwfgCy0s+itJUfXrgVgzIQGmnb2lBrjanWmoQ1OZv0pWfnExFoZOH4jty3vJDFLz1YZ393TtutrZKwJLCuYXCij6MtG+KrdlBK9QU6aK3d87GJ8Liga2eQHnulXdst1s9Z8J+/cr7UYaFTIYRwjcJMCnPOsf1IBv+a9z966X0MNmzjasP2Gl1XWfs5vMXvhqRIkiqE8Kjy0cfqr2Y3ZdcJFosFv6gE/KIS8AmOoN/ji+n/2EJCI6N4/v3lPPbKHJLaxzL0mqucvmfVpK++fpWFkQz19ndGenY+Nz32Jhk5BU6fr1pJePnXm+3OOfuziLo5M6Ja55YNSikD8E9gcr03ki0bmg+DkahJc8h+9XLCiisLn96X9zqvzu3GHyePlzeBQgjX2/0x1qX3Emguog/QB8DPcdd31Dg2+V9ORJXfRQE+Rkb3iuO2Szo4vkgIIdykKU3ZBdevda16v6z0s/gERwBg9A+s0XfzZwsxndnJAd2Nc1l5tA2v+5nObh/jisJIjtS3x6qj87VVEm7sVjiikjOJan1bNoQAPYC1ZYlLLLBMKTWmekEl2bKhmQmMIOSuBZT8Zyi+ugQAP1XK7YefIG1jN0YN7OnlAIUQLc6a5zGYi+rvN/Z17u47kbvdH5EQQjQ5zmw94+rEufo0YEcVhQHysjP5+ZulvH5jPFM+OsTH637mN6NS67y3s9vHuKMwUn2JpaPzWutaE+bGboUjKjmTqNa5ZYPWOgeIKj9WSq0FHpGqvy2DsV1vSka9Ast/W9HWXqVz/PPfkt3jC8KCA7wYnRCiuTuWWcjRzEIuSYzAVxdDlYq+tWoTDz1ucn9wQgjhAq7ezxRcv/WMK23+bCHXp0BydADje/gy98sf6kxUL2SU1B2FkepLLB2dBxwmzK8vXsPaTTtcPuLbWtWbqF7Alg2ihQpIvYPsI1sI2/luRdtAfmTNBw9z9f3/9mJkQojmbN2BdCa/v5kSs5Xu7dqwbHwkjupIlmgj6SEXExsagCGsA1z5CPjIh2RCNFR92w4qpfyAOUB/IAO4VWt92NNxNkdaaywWM9pixWIxY7Vayc3JpuMdz6OtVrS2gtWCtlo5unAmJw/vx2qxYrWYefeFxygsLAQ0tg3QNKDxDwhgwr0Poy0WtNVMUV4u+acOcnbTMkw+vmgUxoAQfMPj0A62g/Ekq8XMz98s5elbbdvG3N4/jHdfO0BGTkGtidqFjJK6ujBSfUlybed9/YNJz6qZMJutPzCpt69sheMiTu2j6syWDVXaBzc+LNHUhN3wIieObCM+d1tF29Xn5rFvzWV0uXqiFyMTQjRX//hyHyVm25uq3Sdz2bb9CI4+cy/ofx/txjzv2eCEaKGc3HbwbiBLa52slLoN+Btwa133TT9zilOnMrCWJWeVXy22l9WCttoSLW0xg9XWhsWM1Vp2bLGiLaVobUGXJW/aaqn4avvedp3StiTOoAANSmkUoMqSu/KV64qq7fZfDQrbxbqsXZX1L0sSlap2Xdlz7I4rnmVrNyiNj9GI0aAwGQ2YDAprfgbnd3+BMhhQyoAyGFEGA8aSPJKPLCnrq7Dkp5MyYipKGTAYjGCwfT306SwmROwr62dk7mfr6RhihqyDxA0YCRpKi/IpOPsT5txz7JnzGKX4cl77UGrwIzi6A0GxnYjtmEJIWERD/+nYqW39q4+liOtT/IgM8gEgMsiHPu18eWX+Vzx771iH93Ln9jH1qS9Jru088V0dxjbm4Vl8uDPdKz9LS+RUoioERh+ifv0h6a9eRpTOqmiO//phchO60KbzAC8GJ4RojrYcybI7PvbL7hqJarYOwtJfVqIK4ULObDs4FphZ9v1HwCyllNJa11pfJOb4l3D0ACajAaNB4WNUtsSq7HuTQWH0MZSdr/xqNFb53qAwmYxl35swGf0xVutvMtquaU4FHf/z6Xo6DRxRoz1vyzLuGFJZ7+PR2SuJuah/jX6n/P0Z0K0jYBsB/GHXz/xtWBCPrN+Oz69uxjfQNtoX1j6Z7I1L+OevK3dtMJstHD2TxYGT69iyajm7sqwEJvXj4suvw8+/9pkpedmZLHjpj0x49O8Eh4bXOF/blOW3Hp3Iwh+PsvDH4xVtJaVGjn6/u9ZE1Z3bx9SnviT5QpNob/4sLZEkqsJpfmHt2D/iP7RJuxVfZduiJojzlP73Ohj9IqT+2ssRCiGas7Dzx2q03VHyJIuipEq8EC7kaNvBS2vrU7YELAeIBNKrdqq6m8NbT9/HtOG93BWzKFM+wpcUbmRsiuLLH76gw5W1r9k3mYx0io+iU3wUwy+xtW3bd5wFH83kTGkgMX2G0an3QAwG+x0ry6v2bkpbwDUT7nM6vntenFtzTa4PpGel0+6m51g36z4S4yIv6Gd2p/oSS0k8vUsSVXFBelw6jLTdD3Hd0Zcq2nwoRS9/CBXdDRIGejE6IURzFlF8wu74npI/sIdEAn0drVwVQjRQndsOXkAfu90c2POJJvtoo4MT9koKcslOP0NGToFdpdlzGSVc3z6XxUs/Imv3txiNtt+TUSG17OdVRd8u7enbpT1ms4XPt2zgs/c/ptA/hs5XjiOmQ5Jd1d77ly9lwHW3ORxVrU1thZ4OvPVbBvz+PYoK8u2mY/sYDUS2CWD5XyfTMTYCXx9JT4SN/EsQF2zYpMdZ/tIeRhevqGhTaPjkfrj3e/Dx92J0Qojm5nLDTn5l+JHeJVvt2g/rGIJ9Tc1qip8QzUB92w5W7XNcKWUCQoFMz4TX8kSF+LH7Pw87bK/Pma1f0jG4tEal2ajgtnQFHsjIgfjeDVr/aDIZGT3wIkYPvIic/CLmrf0vm1YWsefIOYZ2tJAcHcD1KQUXPKpaG4PRCMYguv+2sjintlopzcvk4H//xCs7gyhYvR+T5Ty+lOBLKYFGTVJ0MCmxwSTFRRIfFYrJVPuHlwPue530vOIa7VEhfmx64/5G/wzCsyRRFRfMx2SE617iqUXRPOfzXuWJjAOw52PofZv3ghNCNCuXqr184PM3TKpmpcqjOppQP/kzJYSL1bntYJllwF3AeuBmYHVd61NF3ZxNkKontBaLBZV3hn+PDubvX2/GLyCYc5nuKToUGhzAb0f3Jz07n+sffBnfjgZeWHGYzrGBfPL1/y54VNVZymDANzQKX/9A+gwfX+O82VzKM78dT15ONtpcgtVcWjESG+hnZNq4q+kcE0JKbAiJsZGcyz1Pj2n/qHGfr/42jU4Ta7ZLAtu0yTsA0SAjesTxl7TrmV9wmAmmNZUn9nwiiaoQol6lFltiOtPnA4dJ6mkdThH+xPvLnykhXMnJbQffAf6rlDqAbSRV/rB7QPWE6R/zvoATP3Bdn1B+ys2ptdKsK81ZsY5buvny0K9C0Vrz/eHzBJdk8vl7f+fmBz1ffd1k8qG4pJSLf/dujXMH3/4dsTfO5OiZE+w4dYTCA4dJz85n11dLUFgxACZfX4LCozGXlpJyx0x8AoLtZuk4GukWTYe8AxANYjIauP+aZOZ+PNQuUbXu/wpDcR74hXgxOiFEU1eYdZr/+vyFrgbHa9p2WxMBCJIRVSFcrr5tB7XW54FbPB2XqFTX/p5aa+55YS6zH7+z1r1JG8pRlVutTRzfuNqlz3GkRhGmMtnnTtd6jY+fH7EJnYhN6ATA/5YsIWZIZXFPS3ERxVmn0Fqzf9tGrEW5ZVsKWVFosnPy+N+3e0iOCyUxLoI2QbJHd1Mi7wBEg912SQLzN/biWHpbOhjOAWCwlsDPn0Mv+fsmhKid36f3caVxV63nd1g7AxDsJ4WUhBDNX3p2/gUll3Xt7wmQdfpYxV6frlRbldsXFm8gNzOdNhFR9d6jtj1Wg4NDHCai5WorwvTDC3Vu4Vsno18AgbGdUCZfoi+zr46stSbnwDa2Roxg7ZHDFGw+gi7KxZdSfCnBDzPx4QF0jgkmuV04iXERBPj5NjgWceEkURUNZjQonhrdnbR3B3CPobKwUtHqvxHQ/UYwyj8vIYQDp37E/8jaOrv8qG2fjgfLiKoQogWYs2LdBSWXte3f2fbEXoqL8nljXBT3LbeNsLp6VNVRUj3u0k68svkr+l5b/yzw2vZYBduoaUOSWHdQSmEwGul4UU+4qGeN81prcjPTWXf6OF/sO0T+t4dRJfn4KTO+lOJvsJAQGURKbDCd4yJIiI2w1XERLiPvAESjDOwUyZK4MVjPpmFQtsXtAdn7Ydt/IXWKl6MTQjRFZ1fPIrqePjustkRVpv4KIZq78mm8F5Jc1jayWb5u9aJoP0Ynn3fLqKqjpLpLQjTnP9/U6HvXlcQ+OXl0o+9f22iu0jVrIdRHKUVoZFtCI9tC9741zlstFrIzzvDVqWN88uMh8r/6GR9rcUXF4iCTplN0CMmxwXSKi6RdVChGo8HBk0Rt5B2AaLSbRg5jybtXcovpm4q2ou/+TYAkqkKIanIyzxGyf2m9/bJoA0CIJKpCiGaufBpvY5PLutatumpUta6kOsJ0HnNpCSYfz05/NShDraOw1dWWCNc1ktvguIxGIqLbERHdDri0xnlzaQmnz55i96mjFG08RFHGHkzWYvwoxU+ZaeMHnaPbkBIXQmJcJDERIbIdWzXyDkA02sBOkcyJv4cbT39XUb0zIHsfnNkDMd28HJ0QoknQGpRi16f/4nJKKppP6ggeKJnOR37PVLQtMA+u+F5GVIUQzZkrk8u61q26alS1rqR6WM84Vu3cREq/K1zyLGeFRkbx/PvLG3WPukZy3cXk40t0fEei4zsCV9Y4X3y+iEOnT7D19BEK9x2hOPswvroEP1WKrzITHmAkOSaELu3CSIqLJCwkoNUlsvIOQLjEpGsH8f17PbjK+GNFW86WhYSO+rMXoxJCeNveLWsIXvFbQnQuYeRzebXzH5qHsEVfzHvma7nduIqDOo5/mm+uOC+JqhCiOXNlclnbulVX7KMK9SfVg3snMn/ut25LVOsqwtQS+fkHEJeYTFxissPzRQV57D19gg2nDpO/7RDmgsyK0VhfSolp40dKXAjJcWEkxkYSHOjn2R/AA+QdgHCJS5MieKXNNVxVUJmo6h8XwcgZYJCF5aJ5UEqNAF7Ftrfg21rrFxz0GQ/MBDSwQ2t9u0eDbE6sFsLS7iNOn3J4ukQbWWC5BoA/m+/iBfMEirGfUhYi+6gKIZqp9Ox8Xl20hvAgHz7cWWx3riHJZW3rVl2lvqTaz9eHIEuO257vjVHPpiwgKIT2nS+mfeeLa5zTWpOfk8XmU8dZffAQ+euPQHGebUQWM34GM+0jAm0Vi+PC6Rgbgb+fjxd+isaRdwDCJZRSdLz8FopXzsJPmQEIKz6Jec9yTD3Gejk6IeqnlDICrwPDgOPAZqXUMq31nip9UoDHgcu11llKqfpqArVq5n1fEGd1nKQCfGodRDqhFcfVk1SAIF/5MyWEaJ7mrFhH53ADo4dd4fKCR+7gzIht7/ggzhw7REyHJG+EKMoopQgJiyAkLAK69qpx3mq1kpt5jm9PHydt7yEKvz6IobQAP8z4Gsz4Kwsd25ZXLI6kQ3QYpiZYsVjeAQiXGZnalc++uIIbWFvRVrDmn4RKoiqahwHAAa31QQCl1AJgLLCnSp/fAK9rrbMAtNZna9xFVChdP7vWPzJbrcn8uXRSxXFkkC8ZBSU1+gXLiKoQohlqSKVfb3NmxPaGQSk88cVKYjrc65YY/jp9gsNtaoKDQ2TE9QIYDAbComIIi4qBHv1rnLeYzWSnn2HlqaMUbD1Mwbmf8NUl+GhbxeJgX+gUHUyX2BCS2kUSF9kGg8HzFYvlHYBwmQBfI4dSpsD+tRVtoRnb4OR2aNfHe4EJ4Zx44FiV4+PULOPXBUAp9T226cEztdafeya8ZibjFwKOrHZ4apH5Kh4132PX9uDQFDpHB3P7fzbatcs+qkKI5shVlX6bmujwEFT2TrfdPz8/j05TX6vR7mjtqmg4o8lEZGw8kbHxwKAa50tLijl59iS7Th2l8PtDnM/chY8uxU+V4kMpYf4GkmNCSI5tQ1K7SNqGBbul0JO8AxAuddmgK/n6p152RZWKf5iHnySqoulz9BtWVzs2ASnAYKA98K1SqofWOtvuRkpNA6YBJCQkuD7SJi73fCm5X86ivYNzpdrIO5aRNdqD/EzEtvF32C6EEM2JO7aRSc/O554X5jL78Tu9PjKb0AYK8nIICgmtv7Nolnx8/Yhpn0RM+yTgqhrni4sKOXD6OFvOHKVg72FKcg7hV7Z/rI8qpW2QD51jQ+jaqT09aw7oOk3eAQiXuiQxghn+w7mqtEpRpZ2LYeTzYPLsvltCXKDjQIcqx+2Bkw76bNBalwKHlFI/Y0tcN1ftpLWeDcwGSE1NrZ7stmincoq4ddZqlpUstEv983QAu3Uic8zD+FnXTN6D/EzEOEhUg/2a3poZIYSoizu2kZmzYh1Zp495fGTWUYJ846WJvLHxS/oMvbmeq5sXmXbsPL+AQNoldaFdUheH5wvzctl1+ji707Po2YjnOJWo1lcJUyl1L3A/YAHygWlVC5CI1sNgUET2G0vOhn8TqgoB8C/JggNfwsWjvBydEHXaDKQopZKAE8BtQPWKvh8DE4D3lVJR2KYCH/RolE3c0m0nSCrYQZhvQUVbpg5mUPEsh8WSyoX4mRyOnvo1weIOQghRF1dvI+PN9a6OEuTuSXEUfrUZaFyi6igxzEo/y+ljB4nt0KlR924ImXbsOoEhbQgM6dboOhP1Xu1MJUzgQ631m2X9xwD/AEY0KjLRbI1J7cSn3w9iomlVRVvR5rkESKIqmjCttVkpNR1Yie1DuXe11ruVUs8AW7TWy8rODVdK7cH2wdwftdYZ3ou66TlwJp9Oyn4g+itL/zqTVKic4jumdzuW7bBdnxIdTPvwAPcEKoQQbuLqbWS8td61tgRZKUWk6TxmcykmU8O3PHGUGP446z4sFktjQxcthDNpbr2VMLXWuVX6B1FzXZdoRTq3DebNyOuYmFOZqPoe/AIKMiAo0ouRCVE3rXUakFatbUaV7zXwUNlLOHA4o4Ax6oxd20EdB8CApAjahvgxvFsMv1+w3a5PgK9t5PS5G3sQHx5AQbGZe6/q7JbiDEII0Vy4Y72rs+pKkIf1jGPVjxtJ6XeFS59p9A/k9IKnKI6y3/0tODjEpc8RzYMziaozlTBRSt2P7c2bL3CNS6ITzVbX1Gv45cs4OhtseygatRl2fQSX3lPPlUKI5uxoZiGJ1RLVwzqWsEAfFt1TWVmweqJaXt23jb8PfxpRc3NzIYRojdyx3tUZ9SXIV/dJYv6cb12eqHaf+jIH3/4dz7+/3KX3lfWnzZMziaozlTDRWr8OvK6Uuh14Crirxo1aeSXM1mREzzjmfv4rHjUsrGgr/WEePpKoCtFi5Z0vJT2/hARf+0T1qI7m5n72NYAnDerInPVHAEjtGE67MJniK4QQ1bl6vauz6kuQfX1MBFtz0Fo3i5kvsv60eXImUXWmEmZVC4A3HJ1ozZUwW5t2YQH8FDMKa8YiDMr2P7XP2R1wdi9Ed/VydEIIdziSUYgRCx3UObv234wdwuhL7CsDzhjdjW5xbcgvNnPbAPngUgghHHH1eldnOZMg9+/YhqNHDtAuMcVtcXhyJDQ4OMRh4irTjr3HmUS13kqYSqkUrfX+ssNRwH5Eqzegdw+++6oHvzJW2Rh6+4cw/FnvBSWEcJsjGYW0U+n4qCqFMIKiuXFgzam8JqNBElQhPEwpFQEsBBKBw8B4rXWWg34WoPyP91Gt9RhPxSgaJz07nynPfoBG88GMKQ1ex+pMgjzm0mQeTVvZ4ETVmcTQkyOhMgW46ak3UXWyEuZ0pdRQoBTIwsG0X9H6jOwRyz9WXmmXqFp3LMAw5Gkwyha+QrQ0RzILaqxPJcLpfeq3AAAgAElEQVTzWwwIIWr1GLBKa/2CUuqxsuM/OehXpLXu49nQhCvMWbGO9JNHyD6v3b6ONTI0CFPeqQZfL4mhqI/BmU5a6zStdRetdWet9fNlbTPKklS01r/XWnfXWvfRWl+ttd7tzqBF89AxMoij0deQpyvXnhkKzsLBNV6MSgjhLkfSC+koiaoQTdlY4IOy7z8AbvBiLMLF0rPz+WT1Jmb8ykRkgGbpqo1k5BTUf2EjJIYZyM1Kd+szROvlVKIqRENd0zORNEu1ItHbP/ROMEIItzqcUcDF6qh9oySqQjQlMVrrUwBlX6Nr6eevlNqilNqglJJktpmYs2IdV8WX0DfOxLiLfYjysW0p407jLk3il01fufUZrlA+zbj6S9afNm0y/1K41ciesTz+1a+41bS2ok3/tAJ1Pgf8Q70XmBDCZbYfy2bW6v1sPJTJU76/2J+M6+2doIRopZRSXwGxDk49eQG3SdBan1RKdQJWK6V2aq1/qd6p6m4Obz19H9OGS7FEbykfTf3bFRYiA32Y1NuXT34uYOmqjfXuuZqenc89L8xl9uN3XvCa1os6xnD+842NDd/tZJpx8ySJqnCr5OgQsqL6czSnLQkGWyVQZSmGPcug351ejk4I0VjFZgvTP9zK8awi/CjhYnXMvkN8P+8EJkQrpbUeWts5pdQZpVSc1vqUUioOOOuon9b6ZNnXg0qptUBfoEaiWnU3B/Z8osk+Wr2L8JDy0dTEcCM+BkVUkGLsRT58e+J8vWtV56xYR9bpYw1e09rWr5jSkmJ8fP0a8yM4JJV4WzdJVIXbXdczjqXfXMHvDUsrG39cKImqEC3AzuM5HM8qAqCrOmpf8TcsAYKivBSZEMKBZdgKXr5Q9vWT6h2UUuFAoda6WCkVBVwOvOjRKMUFW7t1H9t/LuCdzVa7disGLFtr33M1PTuf5V9v5o1xUdy3fHO9o6+OjOgdz/Lt33PxgGsaHH9tnBkJ9eQWNs0hjpZEElXhdiN6xDF9zeX83lSZqOrD36GyDkN4otfiEkI03s4TOQBcpI7ysd8M+5Px/b0QkRCiDi8Ai5RSdwNHgVsAlFKpwL1a66lAV+AtpZQVWy2TF7TWe7wVsHBOQ/dbnbNiHaOTDVwU7cfo5PpHXx25smciH7y/DtyQqDrDk1vYNIc4WhJJVIXbdY0LwRqRzI68TvQ2HARAoWHLuzDsGS9HJ4RojB+P56CwMsun5h9n2sm0XyGaEq11BjDEQfsWYGrZ9+uAnh4OTXhB+WjqovG2abST+gUxftGFj6qaTEaCdR5aa5RS9fZvzMijo2uz0s+y++2H6T71ZadjdoecjHROHN7vsF00jCSqwu2UUozoEce874ZUJKoAbJ0Dgx8Hn4DaLxaitSrIAPN5zpst5BSVejuaWh0/vJ8Rhp2kGE7UPNlpsKfDEUII4aTy0dSoYFs6EBVsYnSyoUGjqoM6hfHzgT10SOleb9/GjDw6uvbE4f1kLP+H88G6iVVb8YtKcNguGkYSVeERI3vEcuvXl/GE6UPCVNmeXkVZsG0uDPiNd4MToikpzoP5E+DwtwD4l72aqsUAvjXb9/d4kJS4Xp4ORwghhJPWbt3HybPFfLjTvqZWuzO1r2mtzehLU1j98VdOJapCOEsSVeERvdqHEhkWxoL8q7nXtLzyxLcvQ987wacpvxUXwoN2L61IUpur8cX/x8zLpnk7DCGEEHVo6LpWR0KDA/ApOuOy+wkBkqgKD7FN/43lne9GMtm4En9VNpUx7xRseQcG3e/dAIVoKrIOezuCRtlh7cTBwF4kRwd7OxQhhBAelBxhIjvjLGGR0R59rtFopDQ/s8bUYU9vYaO0lZPvP+iwXTSMJKrCY67rGcs734Uz1zKUqabPKk+s/Rv0ulW2sRACbFN/q8jVgRTgjwIM9deo8BKF0aA4bEriPyH38q/r+uFrMng7KCGEEFWkZ+dzzwtzmf34nRe8BY0zxg3szIsbVtJ/lGe3H4zt0InCqGief395/Z3dKKxtrFT9dTFJVIXH9O0QTkwbP97IHcOtxrWEKNveixTnwDcvwci/eTdAIZqC4ny7w2fNE1lsGczkyxKZOaZpr/2JBGRDGiGEaJrmrFhH1uljDSqW5IxO8VGUrtgA1F3ZNzg4xGHy5swIaGOudbemHFtzJYmq8BiDQXFt91jmrC/mX+YbedLnw8qT2+bBNf8HfjJdULRyxbl2h/naVhW7Y2SgN6IRQgjRBDR2NLR8K5o3xkVx3/IL34LGWdF+pRSfL6qzsm9jRj7r277Gm5pybM2VzM0SHnX1xbZ1C+9bRnBWh1WeKMmDnYu8FJUQTUiJ/YhqQVnN38RI17+hEEII0TxUHQ2tT3p2Pjc99iYZOQV2149ONnBRtF/FFjTuMKpfew5ua94FAUXTIYmq8KhBnSLxMxkoxcRCy2D7k5vfAa29EpcQAEqpEUqpn5VSB5RSjzk4P1kpdU4ptb3sNdXlQVRbo1o+opogI6pCCNEqVR0NXf71ZrsEtGqf8uS0elJbfv2kfrYPPCf1C6r1Po01qFtHMn/a4PL7itZJElXhUf4+Ri7rHAnAfPM1WHSV6jBndsHBNV6KTLR2Sikj8DowEugGTFBKdXPQdaHWuk/Z622XB1JtjWo+ARgUtA8PcPmjhBBCNH3OjIaWJ6f//mhNjaS2/PqoYNuKv6hgk9tGVY1GA23IR8vAg3ABSVSFx11TNv33JFF8YU21P/n9q16ISAgABgAHtNYHtdYlwAJgrMejqD71V/vTLiwAP5PR46EIIYTwLmdGQ6uOuC75cj1XJ2CX1K7duo8PdxaT+vrZiteHO4tZu3WfW2K+oksU5pLzbrm3aF2kmJLwuFG92vHsir2UmK28Zb6ekcbNlScProUj66HjIK/FJ1qteOBYlePjwKUO+t2klPoVsA/4g9b6WPUOSqlpwDSAhISEC4ui2tTfPALoHi7TfoUQojWqazS0vHJveZ9OET4M6VAKFtte9ZP6BTF+0WYWv/TgBRVOamzhpusuScZk/VQq4IpGk0RVeFxEkC+jesaxdNsJtutkNlov5lLDT5Udlk6DaV9DYIT3ghStkaNdSqvPXfoUmK+1LlZK3Qt8AFxT4yKtZwOzAVJTU52f/6R1jUS1gABC/OVXtRBCtEZrt+7j5NliPtx51q693Zl9PHTH8IrR1EXjQ8jIyefXfX353WcF/PYKi8OktjpHSWljt7EJDvTj5hFX0m/KXy78BxaiCqfe/SilRgCvAkbgba31C9XOPwRMBczAOeDXWusjLo5VtCATB3Zk6bYTAPy9dDyL/Z6pPJl9FF4fAHd/CRFJXopQtELHgQ5VjtsDJ6t20FpnVDn8D+DazX9LCqiaG5/XPlgw4u8j036FEKI1Wvby9DrPVx1x3Z91HqWgdwxc8tpxIkJstQ3Kk9rarq+alLpqG5uL2/qSceYkkTHtLvhaIcrVu0bVyQIj24BUrXUv4CPgRVcHKlqWfglhdItrA8BmfTFfWPrbdyg4B+tneSEy0YptBlKUUklKKV/gNmBZ1Q5Kqbgqh2OAvS6NoNr61DxsbzL8TFJOQAghRE1V159OWAaT0kx8eyaIHp07sOW/M9ny35m1JruOqgm7ahubcYOSObTx88b8aEI4NaJaUWAEQClVXmBkT3kHrXXVUq0bgImuDFK0PEopJg7syBNLdwLwZOmv6W88QCQ5lZ32fgojXwSDjCYJ99Nam5VS04GV2GaPvKu13q2UegbYorVeBjyglBqDbfZIJjDZpUEUVy+kVJao+kiiKoQQoqb6RlzrYp+Unuf1xWtYu2kHi8bb1pGWr3FtyKhqh5hwLOmyTY1oHGcSVWcLjJS7G/jM0YlGFRgRLc7YPu34a9pe8orNnCOcwedfZqd/lW0p88/AsY3Q8TLvBSlaFa11GpBWrW1Gle8fBx53WwDFuXaH+RUjqvJhjRBCiIarvha16tpWsCWlV761jl/3D66zcNOFiAs0c74wH//AYJf+LA3x1+kTyM/Pq9EeHBzC47PmeyEi4QxnPqZ3psCIraNSE4FU4CVH57XWs7XWqVrr1LZt2zofpWiRgvxMjOsXX3GcRyDf+l9t32n7hx6OSggvqr41Df4A+MuIqhBCiEaouha1/LhqNWGAjJwC3tyQ47JtbMb0T+DAlrWuCL9R/jp9AscO/4Lf0AfsXoHX/sFh8iqaDmdGVOstMAKglBoKPAlcpbUudk14oqWbOLAjH6yvrLs1N7cPV/pWmUm+7b/QYxx0rlFYVYiWp1rF33wtI6pCCCEax1GBpOrVhDPzimjfxoDVL5At/33aJc/tf1F7Xv/2B/jVaJfcr6Hy8/PwCY7AL6pyNqe5pJiSzBNkpZ/lycmV8ckIa9PiTKJaUWAEOIGtwMjtVTsopfoCbwEjtNZna95CCMdSYkIY2CmCDQczAVhj7UOGTxyRpacqOy2cBBM/goSBXopSCA+ptkY1X4opOS03N5ezZ89SWlrq7VBEK+fj40N0dDRt2rTxdig1KKVuAWYCXYEBWusttfSrc7cH0bxUX4v6wfLv7da2pmfnM/7RV3ljdCD3LS8kI6egQZV+qzMYDIQZCrFaLBiMTesDVw0ogwmf4Ag6TX2tot3R3q/Ce+pNVJ0sMPISEAwsVkoBHNVaj3Fj3KIF+fXlSRWJagk+TC+axoc+z6K01dahJA/mT4AHtkJAuBcjFcLNqq1RLdC2qb+SqNYtNzeXM2fOEB8fT0BAAGV/h4TwOK01RUVFnDhh236tCSaru4Bx2AYXHKqy28MwbLPqNiullmmt99R2jWi6HK1FrV4gyVEi25A1qY4M7tqWDXu30blHqkvuJ1oXp979aK3TtNZdtNadtdbPl7XNKEtS0VoP1VrHaK37lL0kSRVOG9I1hsTIwIrj9eaLWJ/4W/tORZnw/asejkwIDytxPKIq+6jW7ezZs8THxxMYGChJqvAqpRSBgYHEx8dz9mzTm2Cmtd6rtf65nm4Vuz1orUuA8t0eRDNUfS1q1QJJUJnITupnS1on9Quq2KrGFa5N7czpbatcci/R+jgz9VcItzIaFHddlsifP638sPaxM0P5eqBGbXi9suOGN6HfJIjo5IUohfCA6lN/ZXsap5SWlhIQEODtMISoEBAQ0JynoTu920PV3Rzeevo+pg3v6v7oxAWpvha1XLsz+3jojuF1JrKuGFUN8PMl0Jzd6Ps0ltE/kJPvP1hxbDaXYi3KI6Btey9GJeojiapoEm7sG89fP/uJErNtuu/RzEI2Jt7HwF0f2bapATAXwb/6QpcRMPbfEBTpxYiFcINqxZTKq/5KMaX6yUiqaEq8+e9RKfUVEOvg1JNa60+cuYWDNoe7PWitZwOzAdjziSb7qLNhCg+pb5/V+hJZV+gRF8C5k0dp2847W1MGB4dAfh74V6Y9WemZBLRtT/epL3slJuEcSVRFkxAW6Mu13WP5dEdlQel/rD3OwsFPoJb/3r7zvs/hk/vh9gUejlIIN6s29TdPiikJIS6Q1npoI2/h1G4PomWoL5F1hRsHJjNjzee0vXGa25/liKMqvuX7qlYvnhQcHOKpsIQTJFEVTcbESxPsEtVNhzP5/LLhjOx+I+xeat9532dwagfE9fZwlEK4UY1iSrJGtTVwZvRtzZo1DB48uFHPiY2NZerUqTz33HONuk9Vf/rTn3jxxRd57rnnePLJJ112X+FV9e72IMSFiIsKRWU3rVpcsgVN8yAf04sm49JOkVxzcbRd218//5niUa9CioPpJ2v+AtrhbCQhmqfS83aHRfgCMqLa0q1fv77itXr1agCeeuopu/Z+/fo1+jlpaWnce++9jb5POa01CxcuBGD+fHnT1xwopW5USh0HBgErlFIry9rbKaXSwLbbA1C+28NeYJHWere3YhYtQ3yQpjAvt/6OQlQhI6qiSXniuov5et85LFZbAno0s5D3N6dzzx2LYedHsOTuys77Poct78AlU70UrRAuZim2OyzGB5A1qi3dwIGVe0Tn59umf3fu3NmuvTbnz5/H39/fqee4Itmtat26dRw5coQhQ4awatUqdu7cSc+ePV36DOFaWuulwFIH7SeB66ocpwFpHgxNtHBjL+nIO1tW0evqG70dimhG5GN60aQkR4cw8VL7xfazVh8gPb8YetwE8f3tL0j7I+xY6MEIhXAjs32iWqLLElWp+iuAN998E6UUW7du5corryQgIIDXXnsNrTUPP/wwPXr0ICgoiA4dOnDXXXdx7tw5u+tjY2N56qmnKo5vu+02rrjiCtLS0ujevTvBwcFcddVV/PxzfbuX2MyfP5+goCDee+89fHx8HI6qms1mnn32WZKTk/Hz86NDhw5Mm2a/Tm3x4sWkpqYSEBBAVFQUo0ePrtiHVAjRMvRObkf+oR3eDkM0M/LuRzQ5Dw7tQpsqldnyis3888t9oBTcOBt8gys7ayssnQbLHqixtYcQzY7Zfupv+Yiqv4yoiipuvfVWbrrpJtLS0hg+fDhWq5XMzEyeeuop0tLSePnll9mzZw/Dhw9H17M84sCBAzz11FPMnDmTuXPncuzYMSZMmFBvDBaLhcWLFzNmzBg6dOjAsGHDHCaqkydP5rnnnmPixImsWLGCF198kby8yurWb7/9NuPHj6dbt24sXryYd955h6SkJDIyMi78P4wQoslSShFuKMRiNns7FNGMyNRf0eSEB/nywJAUnluxt6Jt/qajTBqUyEWxyXDDv2HxZFuSWm7rB3D4W7h9EUSleD5oIVzBXGJ3WDH1V0ZUL0jiYyu8HQIAh18Y5Zb7PvLII9xzzz12be+9917F9xaLhf79+5OcnMzmzZsZMGBArffKzMxk48aNdOzYEbBNJZ4wYQKHDx8mMTGx1utWrVrF2bNnue222wDb6OykSZPYsGFDxZTlHTt2MG/ePN566y27UdTyRLi0tJQnnniCCRMmMGfOnIrzY8eOdfK/hBCiORnaM461uzaT0meQt0MRzYS8+xFN0qRBiSRGBlYcWzU8s3y3bXSg21i46W0wVPucJfMgzEqFZ6Nhy7sejlgIF6g2olpSsUZVflWLSqNG1UyAly1bxsCBAwkNDcVkMpGcnAzAvn376rxXly5dKpJUgG7dugFw/PjxOq+bP38+YWFhjBgxAoAbbriBgIAAu1HV1atXYzAYmDRpksN77Nq1i3PnzjFlypQ6nyWEaBmG9E3i7I9rvR2GaEbk3Y9oknxNBh6/rqtd2/cHMvi/T3ZhtWrbetW7v4RIB6OnlmJY/gf47p9SFVg0L5ZqI6pla1RlexpRVUxMjN3x999/z4033kjnzp2ZO3cu69ev55tvvgFsI6R1CQsLszv29fWt97ri4mKWLl3KyJEjKSwsJDs7G4vFwpAhQ1i0aBEWiwWAjIwMwsPDay32VD69Ny4urs4YhRAtg5+vD4Gl2fUuSRCinCSqoska3i2GgZ0i7NrmbjjKm9/8YjuI7wf3fAO9bnN8g69mwgfXQ1GWewMVwlVqWaPqa5Rf1aJS9X1XlyxZQkJCAvPmzeP6669n4MCBREdH13J146WlpZGTk8P8+fMJDw+veC1fvpzTp0+zdu1aACIjI8nKyqo16Y2MjATg1KlTbotVCNG09EsI4fTRg94OQzQTskZVNFlKKZ6/sSc3vbGO7MLSivaXv9jHwE6R9EsIB99A25pVNPzooPrv4W9t61kn/g8MMiolmrjqVX/xwddowGBQtVwgHHHX2tCmqqioqGIktNy8efPc9rz58+cTExPDggULapwbN24c8+fPZ8iQIQwZMgSr1crcuXOZOrXmNmI9e/YkOjqaDz74gGHDhrktXiFE0zF2YDKPr1xJXMffejsU0QzIx/SiSevcNphF9wwiPNCnos1i1fx+wTZyz5clrwYj3PgWTF0NV/0JVLV/1gfXwkvJMG887Fkm04FF02WuuY+qrE8V9Rk2bBj79u3jj3/8I6tWreLpp592mES6Qn5+PsuXL2fChAkMHjy4xuvmm29myZIllJSU0KtXLyZNmsT06dN55plnWLVqFYsWLWLixIkAmEwmXnjhBebNm8fkyZNZsWIFy5cv58EHH+THH38E4IsvvsBkMrFx40a3/DxCCM9qGx6CIVe2nxLOkXdAosnrEhPCSzf3tms7llnEU0t3Va5zUAra94ern4DpW6DtxfY3KcqE/Sth0Z3w1q9g/5ceil40J0qpEUqpn5VSB5RSj9XR72allFZKpbrs4VYLWEvtmkow4SfrU0U9xo0bx7PPPsu8efMYM2YMGzdu5OOPP3bLsz7++GOKioq48847HZ6fOHEi2dnZfPbZZwC88847PP7447z33nuMHDmShx9+mODgyi3GpkyZwoIFC9ixYwfjxo1j8uTJHDx4kKioKACsVisWi0XWtAnRgnRso8jPkWVZon7KW7/8U1NT9ZYtW7zybNE8zVy2m/fXHbZvu74bky9Pqtk5+yjMHgyF9ezFF5kMcb0hZTh0uRYCwl0Wr2gYpdQPWmvXJYDOP9cI7AOGAceBzcAErfWeav1CgBWALzBda13nLzKnf9eVFMJfKovKFGsfLir+gPiwAL5/7JoL/Glal71799K1a9f6OwrhQfX9u/TW7zq32fOJJvuot6MQzcCeQ6d4/adQ+gy7xduhCDcL9jcxYUBCg9cvyYiqaDYeG3kxF8eG2LXN/HQPj//vRyzWah+4hCXAtLXQ61Yw2q/dspNxAHYtgaX32KYHv9YfVj4JhZkuj180eQOAA1rrg1rrEmAB4GhDx2eBF4G6y6leKEvNab8ge6gKIYRoWbomxlJ0bJe3wxDNgLwDEs2Gv4+R1yb0xb/aG/f5m47xxtoDNS8IS4Bxs+FPR2DK57b9V+tiNdsS1/WzbPuxfv8q/LIazuyG0iIX/iSiiYoHjlU5Pl7WVkEp1RfooLVe7vKnO1ifCuBnkqm/QgghWg6lFBGm85hLS+rvLFo1p6r+KqVGAK8CRuBtrfUL1c7/CngF6AXcprX+yNWBCgGQEhPC327qxR8WbqfqIOo/vtxHTBt/bkntUPMi30DoOMj2OrkdPn8cjq6r+0GFGfDljMpjgwmiu0K7frZtcQIibOteEwZB24tsfSxmyDsJoR1sa2ZFc+Pof7SKf2VKKQPwT2ByvTdSahowDSAhIcG5p9eyNU31D2aEEEKI5u7a3u34Ysd6uqRe5e1QRBNWb6Jatm7rdaqs21JKLau2busotjdvj7gjSCGqGtsnng4RgUx5bzM5RbbiM1YNf/zoR9b9ksEzY7sT4u/j+OJ2feDXn0H+WTifC4XpsP8LWzXgjP21P9RqhtM7ba+tH1S2KwP0vh2CImHbXFuCG90N+txhS2jb9QWfgPp/qINfw+pnweQPQ/9sKwwlPO04UPWTjvbAySrHIUAPYG3ZPpaxwDKl1Jjq61S11rOB2WBbo+rU0832nywX6/IRVUlUhRBCtCyDeycxb873kqiKOjkzolqxbgtAKVW+bqsiUdVaHy47Z3VDjELU0C8hnFdv68OU9zfb7TazdNsJjmUW8uFvBuJb1xv84Gjbi2RIGAhDZkDuSVh6Lxz62vlAtBW2z7VvO7sHvnjS9r1fKPS+zVao6XwOnM+2fUUB2jbdM+sw7FxsS4YB3r8ObnoHuo6GvDO2KcgmP7jyIfCzX6MrXGozkKKUSgJOALcBt5ef1FrnAFHlx0qptcAj9RVTclq1EdUSmforhBCihfIxGQm25KC1RsksNFELZxJVR+u2LnVPOEI4b/BF0fzrtr48sngHxebKz0i2HMliwF++4pVb+zD4omjnb9imHUz6BI5ugGMb4Nw+WxKZewKyjzQsyOIc2PSW7eUs83lYeAd0HQN7l1W2H/7WttY275StAFRQFHQZYftarqTQlgwHtQVj2ajyzo9g/eu2CscDptmmJbfra9t/1t2sFs88xwW01mal1HRgJbZlDu9qrXcrpZ4Btmitl9V9h0aqsUbV9utZRlSFEEK0RAMSQ/nl4D7ad77I26GIJsqZRLXOdVsXokHrtoSow/W925EUFcTvF2zjl3MFFe3ZhaVMfm8zs27vy+he7Zy/oVKV61mrKsyEk1vhxDbb14NfQ2mB43u4yt5qedHxzfBspH2bwcc2IhzaHjIPwrFNgAafQOg3CToPgSVTbW0nt8LORbbret4C4/4DRVmw8S3w8YfUX4N/aP1xZR4CSynsmG8rNNU+FXrcBJGd7fsVZcP822xx9Lnd8b2aGK11GpBWrW1GLX0Hu/ThNar+2qpV+8s+qkIIIVqg6y9N4eFPV0qiKmrlTKJa37otpzVo3ZYQ9egRH8pH917G9bO+43iWfXXe6R9u48s9Z/jTiItpF+bEWtHaBEZA8lDbq1zWYdu61Kwjtmm7YR0gPAnO/WSbRvzzZ2AtbfgznWEttY20VldaCBvftL0c2bkYkq6CtX+1jRgDrHsN+k60FYMqygb/NraE9+Q2yPwFIlNs35+oNtN1/0pY8zx0GAhXPGgrOFVaCAtut02DPrbRdp/uN7j2Z29pqhdTkjWqQgghWrDwNoH4Fpz2dhiiCXMmUa1z3ZYQTUF4kC/zpl7KHz/6kU2H7PdA/WT7SVbtPcvfburFqF5xLnxoIlzzVO3nM36BVX+2JbT+oWWvsMpRS6vFVszp3M+2Ik8D7rFNOU77o23tq7stm25/XJhhWw9bm4Nr677fsQ22EdTqtNU2qhsYCUlXXnCYrUb1Ykqyj6oQwsWUUrcAM4GuwIDa1tgrpQ4DeYAFMGutUz0Vo2hdEsON5Gam0yYiqv7OotWpN1F1Zt2WUuoSYCkQDlyvlPqz1rq7WyMXopqOkUEsumcQb397kOdW7LU7l19s5v4Pt7L3VDJTLk8kMtjP/QFFdobxcy7smtgetpHOXf+zjWLmnrS9Mn9xT4yeEt8P4np5O4qmrUYxpfI1qjL1VwjhMruAcYAzhROu1lqnuzke0X7YRj8AACAASURBVMrdPKgzL2/8gn4jZQxM1OTUR/Va6zStdRetdWet9fNlbTPKi4torTdrrdtrrYO01pGSpApvuvuKJP5+S2/ah9ec6jtrzQH6P/cVd76zkcPpbl5j2lBRKTD4TzBuNkxeDg9shSdOwuQVMOY1GPE3uPd7+L90uH2R7XjMazBmFty3Dp46CyNfhOAYz8Qb16fu80lXwZ1LnVv/2prVKKZkW6MqU39bvtGjR9OzZ89az0+fPp3w8HCKi4tr7VPVgQMHUErx+eefV7S1b9+exx57rM7rtm/fjlKK7777zrnAy7z55pssW1az1pgzz3SHL7/8EqUUV199tcef3dRprfdqrX/2dhxClEtu35bik3vq7yhaJWem/grRrCiluLl/e8b1jee/G47w7PI9mK32S6K/3Z/OyFe/5eHhXbi5f3vCAn29FK2TfIMg8Qrbq6ou1zruf+k9tuJIZ3bbphfH9LStGy3Kgs8fs60bBVt14MQrIPVuSN8HOceh4CwEhNv6Zh6yPTsk1pb4aiu0vwTi+9tGAMPKiqL9stpWlCnjgK3wVGkRBLeFXrfClY/YijWJulUvplS2RrXWPYFFizFhwgQmTpzI7t276d7d/nNei8XCRx99xLhx4/Dza/hMkE8//ZSoKPdMrXvzzTdJTU1lzJgxHntmXebPnw/AN998w4kTJ4iPj/d4DC2ABr5QSmngrbIaI0K4RcdgKwW52QS1CfN2KKKJkURVtFgGg+KuyxLp1DaIBxdsJ6PAfg1gUamF51bs5bkVe7kyJYqHhnWhb0K4l6J1A6OPbe2rnSS4+wvbekhlAGOVXwGNWT/a+RrbSzRctRHV8qm/YYGSqLZ0Y8eOJTAwkAULFvDss8/anVuzZg1nzpxhwoQJjXpG3759G3V9c3lmcXExS5cuZciQIaxatYpFixbxhz/8weNxeJNS6isg1sGpJ7XWnzh5m8u11ieVUtHAl0qpn7TW3zh4VsVuDm89fR/ThndtcNyi9ZpwZQr//D5Npv+KGmROmWjxrkxpy5o/DuaBISkkRQU57PPt/nTGvbGOqR9sYf6mo+Sed3O1Xm8z+donqcL7qlf9LZv6GxYgiWpLFxwczOjRo1m4cGGNcwsWLCAmJqZiGuuJEyeYMmUKSUlJBAQE0KVLF55++mlKS+v+neVoGu5rr71Ghw4dCAoKYuzYsZw+XbP65ksvvURqaipt2rQhJiaGsWPH8ssvlWvmr7jiCnbs2ME777yDUgqlFHPnzq31mQsWLKBHjx74+fmRkJDAjBkzsFgsFefffvttlFLs3r2boUOHEhQURNeuXfnkE+fyq88++4zs7GyeeOIJLrnkkorR1eqWLFnCJZdcQkBAAFFRUYwaNYpjxyq3jN+xYwejRo0iNDSUkJAQBg4cyOrVq52Kwdu01kO11j0cvJxNUtFanyz7ehZbDZIBtfSbrbVO1VqnThtfywwfIerRJSGakpO7vR2GaILknapoFdr4+/DQsC78YWgKczceZeay3ViqTQfWGr7ae4av9p7h/z7eRUpMCFd1acuwbtH06RCO0eBoS2EhXKSWqr+hMqJ64WY2kfXQM3Oc7jphwgQWLVrEDz/8QP/+/QEoLS1l6dKl3HHHHRiNtqJa586dIyoqildeeYWwsDB++ukn/vznP5Oens7rr7/u9POWLFnCAw88wP3338/111/PmjVr+M1vflOj3/Hjx3nggQdISEggJyeHN954gyuuuIJ9+/YREhLC7NmzueGGG+jatSuPP/44AMnJyQ6fmZaWxoQJE5gyZQp///vf2b59OzNmzCAzM5NZs2bV+O8xbdo0Hn30UV555RVuvfVWDh06RFxc3ZXb58+fT2xsLIMHD2bChAk89NBDHDhwwC6m999/nylTpnDHHXfw9NNPY7VaWbVqFenp6XTo0IHdu3dz+eWX061bN9566y0iIiLYsmULR48edfq/b3OmlAoCDFrrvLLvhwPPeDks0cIlhUJediYhYRHeDkU0IZKoilZFKcWdAzvSuW0QL3+xj1/O5ZNdWHMkwmzV7D2Vy95Tubz59S9EBftyzcXRDOsWyxXJUQT4SiVW4WLVq/7qsqm/AU18/bRwiZEjRxIWFsaCBQsqEtWVK1eSmZlpN+23T58+9OlTOaX/8ssvJyAggHvvvZdXX30Vk8m5P+vPP/88o0ePrkgQr732Ws6cOcP7779v1+/VVyu3rLJYLAwbNoy2bdvy6aefcvvtt9OtWzcCAwNp27YtAwcOrPOZM2bMYOjQobz77rsAjBgxAqvVyowZM3jyySftktBHHnmESZMmVfzMsbGxrFixgqlTp9Z6//z8fJYvX87dd9+N4f/bu/f4qMo7j+OfXyY3AoSQhISLXERRAkrFRirWSwt4r6CuEWitlGpdd8tr3e66ymprgVpc3Ze162rdenu9xCpRVIRa3eIFF6uCUgVUlEu5JsSEW7jmnmf/mBOY3CdkJjOZ+b5fr3lxzplnzvk9cyY/5pnzPM9JSGDq1KncfvvtFBYW8vOf//xYHWbPnk1BQcGxK79Ao/G1c+bMITMzkxUrVpCa6h9ff8kll7RZt+7CzK4B/hvoB/zJzNY45y41s4HAk865K4BcYLGZgf974vPOuf9tdaciITD9/BH85/t/4ptX/jDSoUgUUddfiUvnnZLNy/9wHmvuuYRnbxrX4gzBgfYcrubF1UX8ZMFqxv5qGbcvWsu6ovIuilbiQrOuv7qiGk9SUlK45pprePHFF3HO39vjhRdeYOjQoY0agPX19Tz44IPk5eXRo0cPkpKSmDFjBhUVFRQVFQV1rOrqatauXcuUKVMabb/22mublf3ggw+YNGkSWVlZJCYm0rNnT44ePcrGjRs7VL+amhrWrFlDQUFBo+1Tp06lrq6OlStXNtoe2DDMyckhOzu73fotWbKEo0ePMm2a/37OAwcO5IILLmjU/Xf9+vWUlpYyc+bMVvfzzjvvMH369GON1FjinFvs3aUhxTmX65y71Nu+y2uk4pzb4pz7hvcY3XC3B5FwOuWkftR+/VWkw5Aoo4aqxL0LRvRj+e3fofCWc/mnCacyLCutzfKVNfW89NciJj/yPhMefJe7F3/G65+VUFlT1+brRFpzpKqWddt3N9qmMarxZ/r06ezYsYMPP/yQyspKlixZwvTp0/GubAHw4IMPcuedd1JQUMDSpUv56KOPePjhhwGorKxsbdeNlJWVUV9fT05OTqPtTde3bt3KpZdeis/n4/HHH+f999/n448/JjMzM+hjBR6zrq6O3NzGt81qWN+3b1+j7RkZjWf/TE5ObveYCxcuZODAgeTl5VFeXk55eTlXXXUV69evZ926dQDs3bsXoM0uxPv372+3i7GIhN4pGcbBfbp1rxynrr8iQJIvgXOHZ3Hu8Cz+5ZLT2X+kmhWbdvPm+lL+b8NuDlXVtvi6LbuPsGX3EZ5b5R+71DctiaFZPUkwGJyZxrRzhnDu8MxGXzRFmvIlGOt3ljEmoEd5NYkk+Yw0dTPvuA6MDY0mEyZMIDc3l8LCQkpKSjh06FCz2X4XLVrEtGnTmDfv+JDBhkZYsHJyckhISKCsrKzR9qbrb7zxBlVVVbz66qv06OHvdVJdXU15ecd7k+Tk5ODz+Zodo7S0FIDMzM6NS9u3bx/Lli2jpqamxX0tXLiQMWPGkJWVBUBJSUmjLtSB+vbtS0lJSafiEZGO+/5FpzP//T+Sf1XrPR4kvqihKtKCvj2TmXLWIKacNYjq2no+2rqPt74s5c9ffE3JgdZ/1d9/tIb9R/1f4j7ZUc6SNbvI7pXCgD6pnNKvJ0My0zg1tzfnnZJFdq8TvyeixJbUJB8ZSfVQf3xblUuiT1qyfuSIIz6fj4KCAhYtWkRxcTF5eXmMGTOmUZmKiopm91N97rnnOnSc5ORkxowZw5IlSxqN+XzllVeaHcvn8zUa91pYWEh9fX2jcsFc7UxKSmLs2LEsWrSo0aRNL774Ij6fr93xre156aWXqKmp4Q9/+EOz+6bee++9FBYWMn/+fEaNGkX//v155plnuPzyy1vc18SJEyksLGTevHmdunetiHTM0P6Z1Jd9EOkwJIqooSrSjuTEBM4fkc35I7L5xfdG8e6GMp5duZ33Nu1pNnNwS/YcrmLP4So+Kz5+lSfBIG9AOqlJPiqq6zi9f2++N2YA3z41m8qaOmrqHB9t3cdZQzIYlNH2+FmJDRnJ9RDwXb+KZN1DNQ5Nnz6dRx55hMWLFze6atrg4osv5rHHHiM/P5/hw4ezYMECtm3b1uHj3HXXXVx//fXMmjWLyZMns3z5ct56661GZSZOnMgdd9zBzJkzmTlzJp999hkPPfQQ6enpjcqNHDmS5cuXs2zZMjIzMxk+fHiLVzXnzp3LlVdeyc0330xBQQFr165lzpw53HrrrZ3uartw4ULOOOMMfvCDHzR7rqysjKlTp7Jy5UrGjx/P/fffz4wZM0hOTmbq1KkAvP322/zwhz9k7NixzJ07l3HjxnHRRRfxs5/9jKysLD755BNyc3OZMWMGdXV1pKSkMG/ePO66665OxS0ijY3I8lG+p5SM7Nz2C0vMU0NVpAN8CcbEvFwm5uVyqLKG1dv3s2Ljbv60roSyQ1VB76fewRe7Dh5bX19ykMWfFjcrl5qUwL1Xn8m3Ts5kV3kFAGee1Ie0ZP3pxpr0pMYN1WoSNT41Do0fP55hw4axbdu2Y5MCBZo7dy579+7lrrvuwsy47rrreOihh7j66qs7dJyCggJ++9vf8sADD/D0008zYcIEnnjiiUZXGc866yyeeuop5s2bx8svv8zYsWN5+eWXmx3rnnvuobi4mIKCAg4ePMizzz7LDTfc0OyYV1xxBc8//zy//vWvWbBgATk5Odxxxx3MmTOnQ7E3VVJSwooVK7jvvvtafH7y5Mmkp6fz/PPPM378eG688UbS0tKYP38+L7zwAr1792b8+PH069cPgLy8PN577z1mz559bAbh0aNHM3/+fACcc9TV1TW7siwinff9C09j3oo/cs7Vrc/wLfHDGmYX7Gr5+flu9erVETm2SKg556isqWfn/qNsLjvM7kNVvLdpD29/VUqo/8R6pSQydkgGBypqSE9N4rxTsxiW1ZPc9FR6pyZSVVNPWoqPoZlpJPq633xpZvZX51x+pOMIlWBz3c7/upTB+4/PfHpj9Z0knXYxT/3onHCGFxO+/PJL8vLyIh2GSCPtfS5jLdexfomjPD7uNSvhdcvjH3DOjzXZdCzolZrI9HFDTngMky7LiISAmdEj2cdpub05Lbc3ADPOG8buQ1UU7T9KZU09m8sOsXN/Be9uKGNj6eETPtbhqlre23R8Vry/bG55hjwzMCCzp3+M7DeH9qWqto6qmnoOVNRw4Wn9GDUwnd6piZzar1ejRu2BihreXF9KjyQfF4/KJTmx+zV4u5uevsYTdlW5ZLLV9VdEROLMyGwf+8tK6Juj2bfjnRqqImHUr3cK/Xr7J+MYf4p/tsl/v3wkX+w6SHF5BX16JHG4spZH393MpztCe19W58DR8hhZgLe/Oj77Zo8kH5k9kzGDAX1SWVt0gOra493aLh6VS/7Qvlxx5gBO6tuDv+0+zIGKGtKSE9l7uJoeyT7OHNRHDdpO6GGNG6r+rr/JEYpGREQkMqZdMJJfLl/KuGv/PtKhSISpoSrSxcyMMwb14YxBfY5tmzAyh9Xb95PoM+rrHVv2HKGu3vHKJ0Vs2X2EhAQjPTWRrXuOEMT8TR1WUVNHsTcGtmh/RbPn31xfypvrS7nvjfZvxj00K41vnJRBdq8UhvfryVmDMxjZv3e37IbclZKbNFSrSKJXim5NIyIi8WVgvz5Y+eeRDkOigBqqIlEgIcEYd/LxWTLzh/mXp48b0qjckapa1uws53BVLcm+BLbuOcLm3YcpPVBJ2aEqjlbXkpzoo/RgJfuOVHdpHRps33uU7XuPNtrWKyWRv/5iEimJani1xlfXeDKuKpI4Ul0XoWhEREQiZ3ROMnu/Liar/6D2C0vMUkNVpBvpmZLIt0/NPrb+3VbK1dbV8/ZXZXxVcogVm3azftdBBvRJ5eyhfemdmsjqbfvZWHqI7F4pHKmupfxoTVjjHpyZ1i0aqWZ2GfBfgA940jn3H02evxX4KVAHHAZucc6tD8nBa5s3VNOSo/89ixbOOd1zVqJGpCaqFIkV0y48nbuXLSHrun+MdCgSQWqoisSgRF8Cl47uz6Wj+3PbpBHU1Tt8CS1/ia+tq2fNznIOVdbSMyWRfUeqMDPGDs7gkx3l7Cqv4Gh1Lc+u3E7pQX9jqldKIgMzUqmpczjn2NbkCmpTZw3OCHkdQ83MfMCjwMVAEfCxmS1t0hB93jn3P175ycBvgMtCEkDTK6ouiWvG6pfkYCQlJVFRUUFaWlqkQxEBoKKigqQkTYYmcqJyM9NJOLAu0mFIhKmhKhIHWmukgr9R29DVuKnLzuh/bPnH55/Mqi37yEhL4sxBfRqNOV2+oYxH3tlMalICZw3OIDc9lYMVNawtOsCnO8oZOyT6G6rAOGCzc24LgJkVAlOAYw1V59zBgPI98c9XFRq9cqh3UFFxFF99Nf96+ZkM79crZLuPZTk5ORQXFzNo0CB69OihK6sSMc45KioqKC4uJjc3N9LhiHRr3xiYSlnxdnIGDY10KBIhQTVUg+gOlwIsAL4J7AWmOue2hTZUEYmktOREvjsyp8Xnvnt6Dt89veXnnHNhmQAqDAYBOwPWi4BvNS1kZj8F/gVIBiaE7Oi3/oUE/K1fgGkh23HsS09PB2DXrl3U1IS3G7tIe5KSksjNzT32uRSREzP1gpHc+cYfySmYFelQJELabagG2R3uJmC/c+5UM5sG3A9MDUfAItK9mBm+7nGBq6UomzWxnXOPAo+a2feBnwMzmu3I7BbgFoAhQ4Y0fVrCID09XQ0DEZEYkp3Ri8SDn0Y6DImgYO4Xcaw7nHOuGmjoDhdoCvCMt/wSMNHU90pEupciYHDA+knArjbKFwJXt/SEc+5x51y+cy6/X79+IQxRREQkfpx9Uk9Kd26NdBgSIcE0VFvqDtd0ho9jZZxztcABICsUAYqIdJGPgRFmdrKZJePvfbs0sICZjQhYvRLY1IXxiYiIxJXrLxjJlg+Wtl9QYlIwY1SD6Q4XVJc5dYcTkWjlnKs1s1nAn/GPx3/aOfeFmc0DVjvnlgKzzGwSUAPsp4VuvyIiIhIafdPTSD5cEukwJEKCaagG0x2uoUyRmSUCfYB9TXfknHsceBwgPz+/e0yvIiJxwzn3OvB6k233BCzf1uVBiYiIxLFzhvamaNsmBg4b0X5hiSnBdP1ttzuct95wZeE64B2nu12LiIiIiEgnXHf+6Wz/8LVIhyER0O4V1SC7wz0FPGtmm/FfSdWdFURERETiRWoG9KyMdBQSg/r0hKEZJWT3To50KNJBPZKCuhNqqyxSFz7NbDewvQMvyQb2hCmcaKT6xjbVt3VDnXMxM1Wucl27VN/Ypvq2LqZyXTQws1u8YWaKQTEohiiK4URFrKHaUWa22jmXH+k4uorqG9tUX2lNvL1Xqm9sU32lK0XD+68YFINiCJ1gxqiKiIiIiIiIdBk1VEVERERERCSqdKeGarfsW90Jqm9sU32lNfH2Xqm+sU31la4UDe+/YvBTDH6KoRO6zRhVERERERERiQ/d6YqqiIiIiIiIxIFu0VA1s8vMbIOZbTaz2ZGOJ9TMbJuZfWZma8xstbct08zeNLNN3r99Ix1nZ5jZ02ZWZmafB2xrsY7m97B3vteZ2dmRi/zEtFLfOWZW7J3nNWZ2RcBz/+7Vd4OZXRqZqE+MmQ02s+Vm9qWZfWFmt3nbY/b8hkus5zqI/XynXKdcF0vnN9qZWYF3LurNrNVZTVvKOxGIIWz5PdgcamZ1AX+XS0N07DbrZWYpZvaC9/wqMxsWiuN2MIYfmdnugLrfHOLjN8uDTZ4Pey4IIobvmNmBgPfgnhAf/yIzc2Z2ecC2k72YHj7hHTvnovoB+IC/AcOBZGAtMCrScYW4jtuA7CbbHgBme8uzgfsjHWcn63ghcDbweXt1BK4A3gAMOBdYFen4Q1TfOcDtLZQd5X2uU4CTvc+7L9J16EBdBwBne8u9gY1enWL2/IbpfYz5XOfVM6bznXKdcl0snd9ofwB5wOnAu0B+G+Wa5Z2ujCHc+T3YHAocDnHd260X8I/A/3jL04AXIhDDj4BHwvg5bJYHmzwf9lwQRAzfAV4L13vgHeMd4ANvuQ/wBfBaZ/J8d7iiOg7Y7Jzb4pyrBgqBKRGOqStMAZ7xlp8Bro5gLJ3mnFsB7GuyubU6TgEWOL+VQIaZDeiaSEOjlfq2ZgpQ6Jyrcs5tBTbj/9x3C865EufcJ97yIeBLYBAxfH7DJF5zHcRQvlOua5NyXTc7v9HOOfelc25DN4gh3Pk9Ujk0mHoFxvYSMNHMrItjCKsg8mDYc0EHc3G4/BIYb2aXAC8CNcA051zdie6wOzRUBwE7A9aLvG2xxAHLzOyvZnaLty3XOVcC/v8cgZyIRRc+rdUxls/5LK/bx9MBXXNipr5el56xwCri8/x2Rry8L/GY7+Lxb0G5LobqGwNayjtdKdyfhWBzaKqZrTazlWYWisZsMPU6VsY5VwscALJCcOyOxADwd15OesnMBofw+MGIllww3szWmtkbZjY61Dt3zr0HvAUsBs4AvuecO9zwvJk95g0LCXom38RQBxkGLf3qEmtTFX/bObfLzHKAN83sq0gHFGGxes4fA36Fvy6/Ah4EfkyM1NfMegEvA//snDvYxg+mMVHfMIiX90X57rhYPefKdV7RFrZ1u/pGmpm9BfRv4am7nXNLgtxNs7zjXYHqqhg6/VloK4YO7GaI9z4MB94xs8+cc3/rSBxNw2phW9N6hfvvIJj9/xFY6JyrMrNb8V/hnRDCGNoTDbngE2Coc+6w+ecNeBUYEYbjbAYmAbc554qaPLcQ/9CQr4PdWXdoqBYBgb98nATsilAsYeGc2+X9W2Zmi/F3Yyg1swHOuRKve0BZRIMMj9bqGJPn3DlX2rBsZk/g77cPMVBfM0vC/8XtOefcK97muDq/IRAX70uc5ru4+ltQrovt89vVnHOTQrCPlvJO0A3VEMTQ6c9CWzGYWVA5NOB92GJm7+LvFdCZhmow9WooU2RmifjHLoayi2q7MTjn9gasPgHcH8LjByPiucA5dzBg+XUz+52ZZTvn9oTqGF5vhR/jHyd8M/BkkxhWeOWC3md36Pr7MTDCmzkqGf9A7JDMVBYNzKynmfVuWAYuAT7HX8cZXrEZQLC/GnYnrdVxKXCjN0vaucCBhi4t3VmT8QjX4D/P4K/vNPPPjHcy/l+4Purq+E6UN9bkKeBL59xvAp6Kq/MbAjGd6yCu811c/S0o18X2+e1u2sg7XSnc+b3dHGpmfc0sxVvOBr4NrO/kcYOpV2Bs1wHvOOdCeTWx3Ria5KTJ+MeXd6WI5wIz6+/lMMxsHP424N62X9Wh/V8MPAL8BLgV+JYFzAB8wlqaYSnaHvhny9qI/1efuyMdT4jrNhz/Lw9r8c+Odbe3PQt4G9jk/ZsZ6Vg7Wc+FQAn+gdVFwE2t1RF/F4lHvfP9GW3M5Betj1bq+6xXn3X4k9aAgPJ3e/XdAFwe6fg7WNfz8XdhWQes8R5XxPL5DeN7GbO5zqtfzOc75Trlulg6v9H+wP9DSBFQBZQCf/a2DwRe95ZbzDtdGYO3Hrb83sZnMB940ls+z/scrvX+vSlEx25WL2AeMNlbTgUW4e8S+hEwPAyfg/ZiuM8792uB5cDIEB+/pTx4K3Cr93zYc0EQMcwKeA9WAueF8NijgXLg3oBtbwIftVLeBbtv814gIiIiIiIiEhRv3PcqYDVwvWtomZtdCPwf/gmV/tTkNc45F1T/XzVURUREREREJOw60lDtDmNURUREREREpJsysyfNrMhbLjKzJ9t9ja6oioiIiIiISDTRFVURERERERGJKmqoioiIiIiISFRRQ1XaZGZzzMy18rghAvE4M5vV1ccVkdimXCciIhJdEiMdgHQLB4DLWti+uasDEREJI+U6ERGRKKGGqgSj1jm3MtJBiIiEmXKdiIhIlFDXX+kUMxvmdVH7vpk9a2aHzKzMzH7ZQtkJZrbKzCrNrNTMfmdmvZqUyTKz35tZiVdug5n9c5Nd+cxsvpnt9o71qJmlBOwjw5sCe5e3jx1m9kSY3gIRiQPKdSIiIl1LV1QlKGbW7LPinKsNWP1P4DXgOuBC4Jdmtsc596j3+lHA/wJvAn8HDAb+AxiO19XOzHoA7wI5wFzgK+BU7xHoX4F3gBuAMcB9wHbgAe/53wDnAT8DvvaOdeGJ1l1E4odynYiISHTQfVSlTWY2B2h2xcBzsvfvVuBN59wlAa97ArgCGOycqzezQuCbwEjnXJ1X5nrgBeA859yHZvb3wGPA2c65Na3E44D3nHMXBmx7FejvnDvXW/8c+L1z7r9PtN4iEl+U60RERKKLrqhKMA4Ak1rYvgsY6C0vbvLcK8DNwEnADmAc8FLDFzfPy0AtcD7wITAB+LS1L24BljVZXw/kB6yvAf7NzOqAt5xzG9vZn4gIKNeJiIhEDY1RlWDUOudWt/CoDihT1uQ1DesDAv4tDSzgfZHbC2R6m7KAkiDiKW+yXg2kBqzPAl4F7gE2mNkmM5sWxH5FJL4p14mIiEQJNVQlVHJaWS8J+LdRGTPz4f/Cts/btJfjX/ZOmHOu3Dn3T865/sA3gFXAc97YMRGRzlCuExER6QJqqEqoXNNk/Vr8X9iKvPVVwDXeF7bAMonAX7z1t4GxZjYmVEE559YB/4b/sz4yVPsVkbilXCciItIFNEZVgpFoZue2sH1nwPJoM/s9/rFYFwI3Abc55+q95+8FPgVeNbPH8I/nuh/4s3PuQ6/MAuCnwDJvYpMN+CcxUwbFoAAAAPxJREFUOc05NzvYYM3sL/jHkX0OOOAnwBHgo2D3ISJxSblOREQkSqihKsHog38CkKZ+AfzBW74D+B7+L2+VwK+ARxoKOue+MLPLgfn4Jx85CCz0XtdQptLMJuC/lcM8IB3YBvyug/F+CPwIGAbU4f/SeLlzrqiN14iIKNeJiIhECd2eRjrFzIbhv2XDVc651yIbjYhIeCjXiYiIdC2NURUREREREZGoooaqiIiIiIiIRBV1/RUREREREZGooiuqIiIiIiIiElXUUBUREREREZGoooaqiIiIiIiIRBU1VEVERERERCSqqKEqIiIiIiIiUUUNVREREREREYkq/w89QdlCNn2BagAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1152x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## compile:\n",
    "model.compile(optimizer=tf.keras.optimizers.SGD(),\n",
    "              loss=tf.keras.losses.BinaryCrossentropy(),\n",
    "              metrics=[tf.keras.metrics.BinaryAccuracy()])\n",
    "\n",
    "## train:\n",
    "hist = model.fit(x_train, y_train, \n",
    "                 validation_data=(x_valid, y_valid), \n",
    "                 epochs=200, batch_size=2, verbose=0)\n",
    "\n",
    "## Plotting\n",
    "history = hist.history\n",
    "\n",
    "fig = plt.figure(figsize=(16, 4))\n",
    "ax = fig.add_subplot(1, 3, 1)\n",
    "plt.plot(history['loss'], lw=4)\n",
    "plt.plot(history['val_loss'], lw=4)\n",
    "plt.legend(['Train loss', 'Validation loss'], fontsize=15)\n",
    "ax.set_xlabel('Epochs', size=15)\n",
    "\n",
    "ax = fig.add_subplot(1, 3, 2)\n",
    "plt.plot(history['binary_accuracy'], lw=4)\n",
    "plt.plot(history['val_binary_accuracy'], lw=4)\n",
    "plt.legend(['Train Acc.', 'Validation Acc.'], fontsize=15)\n",
    "ax.set_xlabel('Epochs', size=15)\n",
    "\n",
    "ax = fig.add_subplot(1, 3, 3)\n",
    "plot_decision_regions(X=x_valid, y=y_valid.astype(np.integer),\n",
    "                      clf=model)\n",
    "ax.set_xlabel(r'$x_1$', size=15)\n",
    "ax.xaxis.set_label_coords(1, -0.025)\n",
    "ax.set_ylabel(r'$x_2$', size=15)\n",
    "ax.yaxis.set_label_coords(-0.025, 1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implementing models based on Keras' Model class\n",
    "\n",
    "#### Sub-classing `tf.keras.Model`\n",
    "\n",
    " * define `__init__()`\n",
    " * define `call()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"my_model\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "dense_13 (Dense)             multiple                  12        \n",
      "_________________________________________________________________\n",
      "dense_14 (Dense)             multiple                  20        \n",
      "_________________________________________________________________\n",
      "dense_15 (Dense)             multiple                  20        \n",
      "_________________________________________________________________\n",
      "dense_16 (Dense)             multiple                  5         \n",
      "=================================================================\n",
      "Total params: 57\n",
      "Trainable params: 57\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "class MyModel(tf.keras.Model):\n",
    "    def __init__(self):\n",
    "        super(MyModel, self).__init__()\n",
    "        self.hidden_1 = tf.keras.layers.Dense(units=4, activation='relu')\n",
    "        self.hidden_2 = tf.keras.layers.Dense(units=4, activation='relu')\n",
    "        self.hidden_3 = tf.keras.layers.Dense(units=4, activation='relu')\n",
    "        self.output_layer = tf.keras.layers.Dense(units=1, activation='sigmoid')\n",
    "        \n",
    "    def call(self, inputs):\n",
    "        h = self.hidden_1(inputs)\n",
    "        h = self.hidden_2(h)\n",
    "        h = self.hidden_3(h)\n",
    "        return self.output_layer(h)\n",
    "    \n",
    "tf.random.set_seed(1)\n",
    "\n",
    "## testing:\n",
    "model = MyModel()\n",
    "model.build(input_shape=(None, 2))\n",
    "\n",
    "model.summary()\n",
    "\n",
    "## compile:\n",
    "model.compile(optimizer=tf.keras.optimizers.SGD(),\n",
    "              loss=tf.keras.losses.BinaryCrossentropy(),\n",
    "              metrics=[tf.keras.metrics.BinaryAccuracy()])\n",
    "\n",
    "## train:\n",
    "hist = model.fit(x_train, y_train, \n",
    "                 validation_data=(x_valid, y_valid), \n",
    "                 epochs=200, batch_size=2, verbose=0)\n",
    "\n",
    "## Plotting\n",
    "history = hist.history\n",
    "\n",
    "fig = plt.figure(figsize=(16, 4))\n",
    "ax = fig.add_subplot(1, 3, 1)\n",
    "plt.plot(history['loss'], lw=4)\n",
    "plt.plot(history['val_loss'], lw=4)\n",
    "plt.legend(['Train loss', 'Validation loss'], fontsize=15)\n",
    "ax.set_xlabel('Epochs', size=15)\n",
    "\n",
    "ax = fig.add_subplot(1, 3, 2)\n",
    "plt.plot(history['binary_accuracy'], lw=4)\n",
    "plt.plot(history['val_binary_accuracy'], lw=4)\n",
    "plt.legend(['Train Acc.', 'Validation Acc.'], fontsize=15)\n",
    "ax.set_xlabel('Epochs', size=15)\n",
    "\n",
    "ax = fig.add_subplot(1, 3, 3)\n",
    "plot_decision_regions(X=x_valid, y=y_valid.astype(np.integer),\n",
    "                      clf=model)\n",
    "ax.set_xlabel(r'$x_1$', size=15)\n",
    "ax.xaxis.set_label_coords(1, -0.025)\n",
    "ax.set_ylabel(r'$x_2$', size=15)\n",
    "ax.yaxis.set_label_coords(-0.025, 1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Writing custom Keras layers\n",
    "\n",
    "\n",
    "#### Defining a custom layer:\n",
    " * Define `__init__()`\n",
    " * Define `build()` for late-variable creation\n",
    " * Define `call()`\n",
    " * Define `get_config()` for serialization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0 0.00821428 0 0]]\n",
      "[[0 0.0108502861 0 0]]\n"
     ]
    }
   ],
   "source": [
    "class NoisyLinear(tf.keras.layers.Layer):\n",
    "    def __init__(self, output_dim, noise_stddev=0.1, **kwargs):\n",
    "        self.output_dim = output_dim\n",
    "        self.noise_stddev = noise_stddev\n",
    "        super(NoisyLinear, self).__init__(**kwargs)\n",
    "\n",
    "    def build(self, input_shape):\n",
    "        self.w = self.add_weight(name='weights',\n",
    "                                 shape=(input_shape[1], self.output_dim),\n",
    "                                 initializer='random_normal',\n",
    "                                 trainable=True)\n",
    "        \n",
    "        self.b = self.add_weight(shape=(self.output_dim,),\n",
    "                                 initializer='zeros',\n",
    "                                 trainable=True)\n",
    "\n",
    "    def call(self, inputs, training=False):\n",
    "        if training:\n",
    "            batch = tf.shape(inputs)[0]\n",
    "            dim = tf.shape(inputs)[1]\n",
    "            noise = tf.random.normal(shape=(batch, dim),\n",
    "                                     mean=0.0,\n",
    "                                     stddev=self.noise_stddev)\n",
    "\n",
    "            noisy_inputs = tf.add(inputs, noise)\n",
    "        else:\n",
    "            noisy_inputs = inputs\n",
    "        z = tf.matmul(noisy_inputs, self.w) + self.b\n",
    "        return tf.keras.activations.relu(z)\n",
    "    \n",
    "    def get_config(self):\n",
    "        config = super(NoisyLinear, self).get_config()\n",
    "        config.update({'output_dim': self.output_dim,\n",
    "                       'noise_stddev': self.noise_stddev})\n",
    "        return config\n",
    "\n",
    "\n",
    "## testing:\n",
    "\n",
    "tf.random.set_seed(1)\n",
    "\n",
    "noisy_layer = NoisyLinear(4)\n",
    "noisy_layer.build(input_shape=(None, 4))\n",
    "\n",
    "x = tf.zeros(shape=(1, 4))\n",
    "tf.print(noisy_layer(x, training=True))\n",
    "\n",
    "## re-building from config:\n",
    "config = noisy_layer.get_config()\n",
    "new_layer = NoisyLinear.from_config(config)\n",
    "tf.print(new_layer(x, training=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_4\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "noisy_linear_1 (NoisyLinear) multiple                  12        \n",
      "_________________________________________________________________\n",
      "dense_17 (Dense)             multiple                  20        \n",
      "_________________________________________________________________\n",
      "dense_18 (Dense)             multiple                  20        \n",
      "_________________________________________________________________\n",
      "dense_19 (Dense)             multiple                  5         \n",
      "=================================================================\n",
      "Total params: 57\n",
      "Trainable params: 57\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6oAAAEUCAYAAAAiI8syAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+17YcXAAAgAElEQVR4nOzdd3iTVfvA8e9J2nTvDS0te+8hIDJlKVsZdaC4+YmIvooLAXlFfUUFcYCIGwUREBBxgcXBHjJkIyC0QEtpoXRnnN8fadOmSdu0tE1Lz+e6uK7meU6e5w5KmjvnnPsWUkoURVEURVEURVEUpbrQODsARVEURVEURVEURSlMJaqKoiiKoiiKoihKtaISVUVRFEVRFEVRFKVaUYmqoiiKoiiKoiiKUq2oRFVRFEVRFEVRFEWpVlSiqiiKoiiKoiiKolQrKlFVFEVRFEVRFEVRqhWVqCqKoiiKoiiKoijVikpUFUVRFEVRajEhxEghxGQhRNMixyc5KyZFURSVqCqKoiiKotRSQojXgMeBRsAvQogphU7f55yoFEVRQEgpnR2DoiiKoiiK4gRCiANAeymlQQgRBHwD7JZSPi2E+EtK2d7JISqKUkupGVVFURRFUZTaSyOlNABIKS8Bg4AYIcRHqM+JiqI4kXoDUhRFAYQQHwshkoQQfxdzXggh5gshTggh9gshOlR1jIqiKJXgfOH3MyllLjAWkEArp0WlKEqtpxJVRVEUs08xzyQUZzDQOO/PQ8CCKohJURSlst0LnCt8QEppklI+ANzklIgURVEAF2fdODg4WMbExDjr9oqiVFO7d+9OllKGVPV9pZS/CyFiShgyHPhcmjf2bxNC+AshIqSU50u6rnqvUxTFHme91wEIIeYBT0iz+OLGSSm3OHrNfWcvy5SM3AqJT6k4R376lImD2zk7DKW2cvWA+jeJ8j7daYlqTEwMu3btctbtFUWppoQQ/zo7hmLUBc4Wehyfd6zERFW91ymKYo+T3+tigfpCiFgpZWbRk0KIwVLKH8pywXOXs4hPzaqwAJWKsfPwGe5oDn7eHs4ORamN3HygfvkXZqilv4qiKI6x942g3bLpQoiHhBC7hBC7Ll68WMlhKYqilFlXzO1o/hBCROQfFEIMFEJsB9Y5LTKlQsXcOJyvfz/s7DAUpVxUoqooiuKYeCCq0ONIiuzryielXCSl7CSl7BQS4pSVfYqiKMWSUp4CugPJwA4hxH1CiC3AD8AVoLcTw1MqUER0Q3adyXB2GIpSLipRVRRFccxaYHxe9d+uwJXS9qcqiqJUV1LKK8AbQADwIeAOdJNSDpBS/uHU4JQKJYMakHDxsrPDUJQyc2iPqhBiEPA2oAUWSylfK3J+LtAn76EnECql9K/IQBVFUSqTEGIp5lmEYCFEPDADcAWQUi4E1gO3ACeATGCCcyJVFEW5NkKIgcCLQDdgI+b3tfswLwfe7sTQlErQtOdIvtg0n2dHd3V2KEo5mRBkaAMxurhjfyeSs0m0hmy8jClo7O+KKpdSE1UhhBZ4D+iPeenbTiHEWinlIUtoUj5RaPxjQPsKi1BRFKUKSCljSzkvgUerKBxFUZTK9AMQB/SSUv4JIITYC3wshGgipZzh1OiUCuUXFMK2FJOzw1CuQYY2EFdvf7yFEVEN81QpIUe6k5EOPsZLFXZdR5b+dgFOSClP5jWBXoa5TUNxYoGlFREcQLbeyMFzVyrqcoqiKIqiKLVdbyllv/wkFcx764EhwGQhxDLnhaZUBveoNhw8pXar1FRGF3fcqmmSCiAEuAlj3oxvxXFk6a+9lgw32BsohIgG6gO/FnP+IeAhgHr16jkU4O9xP7Bu0xayYm7mrt6t6dk4GFFd/ytVY2lpaSQlJaHX650dilJLubq6Ehoaiq+vr7NDUZRqK+5IEl/vPEvzCF8m9m6IzsW5pSR+PZLI8p3xtKzjy8O9KieeQ+fSWPjbPwR66Xi8X2MCvHQOPS9bb2TehuOcSckgKtCT+NQs2kf5c2/3GFy0qgRHSaSUvxdz/BchRA/guyoOSalkzXrcyldrZjO7fkTpg5VqSFTbJDWfOb6KDdKRRNXhlgzAOGCFlNJo72Tet3WLADp16lTqAmaTSSJ2fMh83SZyExay+YtWzPYZTIveoxnQNgZvN6e1ga1R0tLSSExMpG7dunh4eKhEX6lyUkqysrJISEgAUMmqotiRcDmL+z7biZTw48ELuLtqeLhXQ6fFczYlkwc+24UpLx4fdxfuvbF+hd7DYDQx/uPtJKfnAnAlS8/cse0ceu68DcdZ+Ns/Vse+338eH3cXxnZ27MtwxZaU8qAQwu6EhFJzuXt6k5DpipRSfQ5UagxHvnJ0uCUD5kS1wpb9/nownhv0OwDQCSN9tPuYlvkaw7/vxPnZbfh+xmA+em0yH3z6Ke/9+BeHz6dV1K2vK0lJSdStWxdPT0/15qQ4hRACT09P6tatS1JSkrPDUZRq6Y9jF5GFvsJ99YcjzgsGWLL9X0yF4pn53aHiB5fTyeQMS5IK8O1fCWTmGhx67tc7z9g9/snm0xURWq0mpVQNoK9DgS168Mf+084OQ6mhfvxjN01vmUijgQ/x2ocrquSejkxJ7gQaCyHqAwmYk9E7ig4SQjTFXOJ8a0UFF5W2C1+RaXNcKySNRQKNSYDsLXD6M4ynBFu3tGBtYAfq1QmnVdsuuDTqC1o166rX6/Hw8HB2GIqCh4eHWn6uKMVIzbT9txGfmklkgKcTooGDCZX/5W+23nYB1tZ/LtGveVipz7X39wVw5MLVa45LUa5HjTv1ZvVXG+nZtmJXRijXP6PRyKMvf8Avi2cRGRZE57H/YVifLrRoVLmrV0rN4qSUBiHEJOAnzO1pPs5bFjIL2CWlXJs3NBZYllcZs0I0bdYGMqeQfWAN7mmnShyrFZIe4iBcPgiXgUNw1q0RO+vew0mvtjRv3IRbWofX2hnF2vq6lepF/X+oKMVz1dr++4g7ksTd3WI4eO4K3+5JoHmEL6M61C33v6X98Zf59q8EWtbx47ZSrmOy8+s812C6pn2qmbkGPv7zFLkGE/f1qE+23rYS6XOrDnBL62QGtAije6Pgct3HYDRV2D7VH/++wI5TKQxsGUaLOr58svk0BqM5/lPJGazZe452Uf4Mb1dHvccp1ZqLq44U6UOu3oDOVU3kXK+63PUCyVeybI4H+3mwY8nscl1zx4HjNKoXQYOocADGDb6JNb9ud36iCiClXI+5h2DhY9OLPJ5ZcWHlCWoI/V/C/eaZcOEA6ZsXoT+2kYDc4lYeW4vKOUHUyRcBOLsvhDXfNEZE3YCMvIFm7btRJ8ALX3fXCg9bURRFUcoqI8d2djHu6EVuaR3ByPe3kGswJ3VGk2RM5yibsaU5dzmLsR9sIytvFtNUynUS07Jtjp1NzaRhiHeZ751v6or9rNtvrjy69eQlHuvb2GZM0tUcPt1yms+3nua7x3rQso6f3WuF+riRdDXH7rn41Cxigr3KHWe+TUeTeGTJbgA+2XKK+sFenLyYAcDKPQkkp+eQYyhItke0r3vN91SUyhTRaSDrtm9iVI8Wzg5FqSTJV7Jo+fBcm+MHP3jCzmjHJCReIiq84IvDyPBgtu8/Wu7rOapmlMUTAiLa4H37uwQ8fxiePYuc8AMZ/V7lfMxIUjxKz+ajNBcZod3C8HNzGbFjHCELWxE3exgfv/wQ3y1dwJW09Cp4IUp5CCFK/bNp06Zrvk94eDjTpk275uv8+OOPCCE4ceLENV9LUZTaI8PO3sx9Zy+zck+8JUkFeHbV/nJdf83ec5YkFWDjkcRixxpNkjMptltvTidnlOve+fKTVICdp1O5cMU2Gc5nkubZ1eJk2Vk2nO/UpWuLM9/cX45ZfpYSS5IK5uJXhZPU1XsTKuSeilKZ6rfsxMZDaguyUjb2FsyKCq7wa0/NnPd390VEd8crujteN/0fAIb4vcTvXs+RU2eol7KFFpp/S7xEkLjKcO0WMABHv+bS0VfZHT2a6BuGEdi4K1KrQ6tRS3iqg61bC7Y9Z2Vl0bdvX6ZNm8att95qOd6ixbV/M7h+/XpCQ0Ov+TqKoijlkZFjm6heyshlx6kUq2Omcm6wiTtqXcgsMc3+bCRAQmoWeqPtjU5dQ6KalWubWNqbtS1sf/yVYquU2rtevlMXM+jTtOwxFrUv3vE+7puOqg//SvUnhCDTPZS0jCx8vVT9EsUxkeHBnL2QbHkcfyGZOqGBlX7fmpmo2uES2Y6YyHbEAAmpmew78DNuJzegO7+LyOxj6ETxv9AAgrhC0L+L4d/FpElPfjW1Y5dbN+66cwKNoyNV0upEXbt2tfycnm6e+W7YsKHV8eJkZ2fj7u5Y8+EOHTqUL0BFUZQKYC9RBfsJpd5owrXwHkyTEQ6sAEMWtBkHru5k5BhY9VcCgZ46bmwUxO5/U62ucTFv2ezfCVfYcSqFnk2CaRTkAQe+IftcMh7UIQvr9883fj7KuC71zO3hcq7C/q+RnsH86dqdHadT0Wk13NwijOYR5hZUm44mcTo5g2Ht6pJjsP493EqcpP4/22gg6pEgg+mv2Y0ben4wdSGz0H3/uZhBo1Dr5cZ6owlDCRn76SIzqkaTZPVfCRhMJka2j0R39SwcXQ9hLSE9CaQJmt4Cbnn3MeTC4bUM0+zhvAyileYUv5g6Ei+L/zLTS6ct9pyiVCf1u4/g69+X8eDg9s4ORakhOrdqzPF/z3Eq/gJ1Q4NY9sMffPX6U5V+3+smUS2sboAndXuOgJ4jALhw6TJ//vYLEVf3E3H1AGGXduAli/9W2FdkMkK7hRGGLeR+Oo81pm5s8r+N/jcPYmjbOlX1MpQyWrhwIRMnTmT37t08/vjj7Nq1i1mzZvHUU0/x1FNP8dNPP3Hq1CkCAwPp27cvb7zxBiEhIZbnh4eH88ADD/Dyyy8DMG7cOOLj43n++ed5+umn+ffff+nYsSOLFi2iadOyfVWfnp7O1KlTWbFiBVevXqVNmza89tpr9OnTxzJm06ZNPP/88xw4cACNRkPDhg2ZMWMGw4cPB2DlypW8/PLLHD16FHd3d5o2bcqbb75J9+7dK+BvT1EUZ8soZobwQILtrN7ZlEwaFN4r+sNU2LnY/POR75F3LOfOxdvZe/YyAA2CvTAWSewuXs1hf/xlRr6/BaNJonPRsLvdenz+/pwmwALXttyrf8bqOdl6E098vZcP7+4Inw+HhN0IYJf+Nt4x3gbAu3EnWP/4Tew8lcKzeUt3P/zjFAvuKvgysK04wUrdTFzOmeivc2WzqSV9tXsB6G/czSP6gr1UcUeSbBLVzBJmU8F25nfa6gMs3XEWgG0HTzD3/L2QU+TvteUoGP2J+eefnoOdi5mvKzg9VX5Nz5y5XCSgxHsrSnUXEdOInRvSedDZgSg1houLlndfeJiBD87EaDJx38ibadm48vtVX5eJalHhQf7cPmo0MNp8wGiAhN1kn97GyUO7qXf+Z7yFbXUsMPdvHaX9k1FX/yR+1Wx2/dmTVsOfxD2yddW9AKVMxo4dy6OPPsqsWbMIDAzEZDKRkpLCtGnTiIiIIDExkTlz5jBgwAD27NlTYpXGEydOMG3aNGbOnImrqytPPvkksbGx7Nmzp0wx3XPPPWzYsIFXX32VmJgYFixYwMCBA/nzzz/p0qULly5dYujQoYwdO5ZZs2ZhNBrZv38/qanmGZBDhw4xbtw4nn76ad566y0yMzPZtWuX5byiKDWfo/1DwTxjaElUTaaCJBXg+M/8Gx9vSVLB3K+0qFyjiRlrD1oS2FyDCd2hbyzne2v30dCQwD/SukDQL4cSOXfwT+ok7LYce8J1JW/nJao5BhMbDiXyxs8FhTYSLmexdEdB39MnXFbiIsz7O92E3pKkAgzS7qSeIZEz0tyiZve/qTYfqEta9gvm5N5okmg1AimlJUkF8Dv+LbjaWdJ7cBXcPAN8I2HP5zanPUQuI7Sb+dA4xO49M3KNZOQY8HKrFR+tlBpOBtbn3MUr1AmxX6xMqbmC/TzsFk4K9ru2pd639OrELb06XdM1yqp2vptqXaDeDbjXu4EWPeHE2fPsWvchQck76GDYR5Cw3zsuUiQTeXEVLF7F37q2iBseomXvcTWuV2vMs987OwQATr92a+mDyuGpp57i4Ycftjr2ySefWH42Go107NiRRo0asXPnTrp06VLstVJSUti+fTvR0dGAeSlxbGwsp0+fJiYmxqF49u7dy6pVq1i2bBljx44FYODAgTRr1ozZs2ezZs0aDh8+TEZGBu+99x5ubm6WMfn27NlDaGgor7zyiuVY4T26iqLUfOl2qv4W51RyoUJHV8/bnL9y6YJD1/nrTEEy60UWbibrL217a/bxj9G2ku2pv7dS0vqiC2nZNntcfyu0h7O3dl+JcfXR7OUzo/k9sOgyXrAtpFTX34Or2XrSss3J/uVMPXvPptIxOpArWdb9VrtqDhd/4+O/QKN+YMy1e3qU9s9iE1Uwz1KrRFWpCZr0HMGS395j6u03ODsUpYKVtwVNdaTeTYFGURE0mmjutpOVncuBPRvZuv4LBmp2Eq1JsvucVrn74I9HSdo8k+N1R+HT9W7atFSzrNWBvQRu7dq1vPLKKxw+fJi0tIIvIo4dO1ZiotqkSRNLkgoFRZvi4+MdTlR37NiBVqtl1KhRlmNarZbbb7+dRYsWWe7j7u7OuHHjuO++++jZsyd+fgXfcrZp04bz58/zwAMPMG7cOLp3746np6dD91cU5dodvXCV05cy6Fo/iO2nLtEs3Jd6Qdb/Bo0myW/HkvDz0NExOgAun4WEXRiiuvP7OfDzcKVjdCBcSYBzf0FkZ/AJszw/084e1WbiDPVEIrtNTeikOcoJWZcg0tCePA/tR8CZrWCyfZ4hPcXmWD4XDPTU7CdV+vCXNLeH8SaTcdo4m7Evui5hnbEriQTQXpygueYMV6QXl+Nt28TFajciAAMaDCl9LccjRRLdNIcgHbaKlsTLEJvnFtVX81deoioJv7QN084TaHzCzH9np//E7cJ57tD+w3kZyCkZzlBxhjqhGg4kmN/fz8tANh2OoWOwJGvP99yh3csRUxR7ZBNSZQntdQ6swHjhb4rbbdpcc4Y7tBs5KSOIlyG0FifZaWpGMub366SrORXSFkdRKpt/cBhbkx1fxaEozqAS1SI83HW07j6YeJ923PLNX/RmHw+7b6BZ1l92CzKFmi4SevYDTGcWcSm8G0E97ocWI7iql/xxPJnWdf2IClQJRVUKCwuzerx582ZGjhzJuHHjeOGFFwgJCUGv19OzZ0+ys0uuOOnv72/1WKczb1gq7XmFnT9/noCAAFxdrXv2hoWFWZbuhoaG8tNPPzFr1ixuu828fG7QoEG88847REdH06ZNG1atWsWcOXMYOHAgbm5u3H777cybN4/AwMqvuqYotdnGw4k89MVuqz2eGgHLH+5Gp5iCf3+PLNnNL4fMLV/m9PZg9F/3QE4aucKT57P+xwWCeL2PJ2P2jIecNPAIgEc2g595xrJoMaX+ml0sdJ2LVtgpGnQSmPOfYmPOuZoM+Ns9t8j1LctS21n6u/nK2JfVuuk00tjvUf672xNkNLuNwKPLCg7a6ej2qutHlp9Npz7ibzGDLNxYpZuBpzAXbjJIDaNzZxQbd76umsN4kM1kl2+ZqP0OiiwEqgO8UvgtNcv8J7bQsa27/4BD8USkxVvGztDfg7Gkznxnt6E9u63E2F4p9DoBLkpfBuf8j2T8SLrq+O8GRXE296g2HD59geYx4c4ORVHsqhl9VJ1gcOsI/n5pMG9Nm0qbZzdy+sEjfBH5Ens1Le2O1whJUOIWWHk/6Qv6cd9rn/B/X+6h/9zfOHjO8fL2yrUruud05cqV1KtXjy+//JKhQ4fStWvXKm1DExERQWpqKnq99fKzxMREAgIKinLcdNNN/PLLL6SmprJ8+XIOHDjAPffcYzk/YsQINm/ezKVLl/jggw/4/vvvefLJJ6vsdShKbfVe3AmbQkQmCS99d8jy+HRyhiVJBTi/Zak5GQU8ZSbPuS4FwHfnfMtxslJh67uW5xQtpvSoyxr7SaoD9MXMqNYh2Wo/6HTXL4jV/lpskgrmPaRWSaoDNJh4zOVbRmn/sCSpAC7CfLw0bkJPW81Ju7O8juqm3wZp8VbH7tJuwF9UTI/VfCEijUHaHQAkldDyR1Gqm2Y9buWrP1XPd6X6UjOqJRBC4OZiXgDUJDKUJg9MAaZwfN82Tv0wl5uyfsVD2O5j8U7eyzfsZatrC9abuvDRD1reun9AFUdfvMraG1pdZWVlWWZC83355ZdVdv8uXbpgNBr59ttvGTNmDGDeJ7ty5Up69OhhM97Ly4sRI0bw119/sWDBApvz/v7+3H333WzYsIFDhw7ZnFcUpWLtKbSPs7ADCVdIzzHg7ebC4fPWtQ1GYJ1gDddu4XH9JAYZfrW+yO5PYdCrSCltZlTbaf4pd8ymjEtAA5vjUcK21+cM1y/KfZ+SdNccxN1k+zuyu+agQ89vKs4SIOxM3V6DGHGBS/hW6DUBBml2sMTYn4vp1T9RFUJ8DAwBkqSUreyc7w2sAU7lHVolpZxVdREqVcXDy4ezGS7F9ipWFGdTiWo5NG7blYatl/H7/uNs+OZ9Rmt/o63mpM24btpDdNMeIvfMF2R99wAeHcZCeBvQutq5qlJZ+vfvz8KFC3n66acZNGgQv//+O8uWlW124Fq0a9eOUaNG8dBDD5GSkkJ0dDQLFizg9OnTloQ5v9jS8OHDiYyM5OzZs3z88cf07Wve5zV//nz2799P//79iYiI4MiRI6xevZqJEydW2etQFMXWn8eTGdQqnMQ06yWf/8g61MM6KbxB2BbxMUnYsWsHrpdP0UaeYz8NMFTEr+bMghnVKJGIDgP/yLoEi6pb4eMu9HTX2n6Z5i70dkbbaqcp+0zPVY0vPib7BREBXIWRlpwu83VL00N7kLaGE6Sl1ogKqp8C7wK2pY0L/CGlLL5qlHLdCGh2I5v//ocerWOcHYqi2FCJajlpNILe7ZrQodkcBs/7A+8rR3nSZQUDtbtsxuqEEXZ/YP7j6gVtx0K/6eb9SUqlGzVqFP/97395//33ef/997nppptYvXo1LVvaX8ZdGT777DOefvppXnzxRa5evUrbtm358ccf6dy5M2AupmQwGHjmmWe4ePEioaGhDBs2zFLlt127dvzwww9MmTKF1NRU6tSpw6RJk5g5c2aVvQZFUWzFHUliUKtwTl/KtDpubx/k127/tTmmMWTSdV1/AFa5wXZTM8blTkNe486cs+fMS3nv0v7CLJdP0QjJ+4ZhuAdEwNVrunSVaS/KnqgeD+xDh+Q1JY7xKaYdXXE2GtvTT/tXqePWuE2Ho0DuedBV39oUUsrfhRAxzo5DqR6adOnLqqVxKlFVSnXfC2+z7rddhAb68ffad0t/QgVQieo18nV3ZdlDXXlsqRsPn42in3EPk1zW0L64b4L1GbDrY+ThdYi+05DNhyE8VcLqKG9vb6S0v2frkUce4ZFHHrF7btq0aUybNs3qWNHrXLhg3c7B3qxrs2bNir1/vkGDBtmM8fb2ZsGCBXaX8gK0atWKVatWFXvNnj170rNnzxLvqyhK1dt68hIAp4r0KS1rMpTvBs0ROolj7JWNrimuAGHORh91WYMmb5/r/7ms5UTAmBqTqMZoEksfVJh3OPrQllBKolpWO01NHUpUAS6KYEKqcZJaBt2EEPuAc8BTUkrH1msrNY6Lq44Ukw96gxFXl+LqXSsK3DuyH5PuHML4Z+dW2T1VMaUKEBXoydcPd6VfszA2mjoyMncWfXLe4n/6cVyQ9pNQkZEE300m5/UmnFz7KpSS/CiKoijVT3xqJjkGo02vT18yi3lG6Zpo4vG3V1a3DPxJR4OJCGFdVKlhxt5inlEx0qQnZ0ylt5+5FkYpeF0/xvZEUCM8w5uV65oXpf0lux8ZBnM8bBBSW6jOgXfxFVJPy+uieuoeIFpK2RZ4B1hd3EAhxENCiF1CiF0/rFhSZQEqFSui4wC+33Hc2WEoFSw5NY3bJs3i0uXit0OURc9OrQj0K6G9VyVQiWoFcXPR8sHdHXlrTFumDmrK18/dScuxMxgp3maafgLrjV24KG0LOLiTS4M9r2FaegdcOEBatp6lO86wbMcZsnIdb/6uKIqiXJtsvZGr2db7Jy/ZFMeRBJCGDj3u5KCTOZy8mMG/hZb+epNJHZFc7jhixAWa+jq2jzNf0d6g/iIdX2yr24pLx2yObTK2tXvNA6aYMsUAcEEGcL/+6TI/L1+a9Cj2nEkKVhp78Ij+CdYYb7QdENSA4OiyJ6rvGYbRO+ctntI/zEpjD17Xj+UzQ3/e0I9mbcA9vHT3QMSdK6DtHXDrWzBlP/SZZvdaIrhRqatuqjspZZqUMj3v5/WAqxAiuJixi6SUnaSUnQbffleVxqlUnJiWnfjl7zKuYFCqvc9X/URqwgk+W/mTs0MpN7X0twK5aDWM6hBpeTykTR261B/I+I8CWHKhPzr0TNSu5VGX1TY9WTXH1sOx9RwyNeeosTPfGHvxx4kGvHdHh6p+GYqiKLXOxsOJPL5sL7kGE88Mbsb9Perz7q/HeePnwomd5D3Xt7k1rxUJQI50Zfa7dwADAXP11zddF+Alyl/9NUZc4JyvHhzMdT81DOAT4yB+cytoVxUg0vF3oGLukJyX+Vs2YLRpE3NcF1mdOyajaF3GwkOp+HBcRjIqZyar3GaW6bn59+wkbJNpgI+Mg5ltMCdDApPtAM8gwiIbkSNdcXOwYNNV7wbMSR4HwApjL1YYe1md//HOG4kM8ISAXtCg0LleT8OORZCRZDW+U4dOUMOrpwohwoFEKaUUQnTBPKlxyclhKZVIo9GQ6RbC1YxsfLzcnR2OUgGSU9NY90scC0aFMfH7OO65bSBB/hVf8byyqRnVShbq487SB7ty5w31cHP34G3jbQzOfY0vDDejl7Z7AbpqDjPT9XM2u02myaH5PPHJRvq+sYmpK/aRY1AzrIqiKBXNZJJMW/036TkGco0mXvvhMP9cTGfeBuulcJ3FUaskFcz9Pqe5LCGANAQmZrp+dk1JKkADcZ5greO9PnFK4csAACAASURBVONlCJeLzqiSToADy4eT8ranXJCBNuf+MUXYHNtqalHi9fLjsLfH1t7vvKJKWjpbeNbYbrEpv0g0Wi3ntbZxF0dTSo2IUJ8SPrT7hNkeC2zo8L2dRQixFNgKNBVCxAsh7hdCPCKEyC/ycDvwd94e1fnAOFnTp4mVUtW/cTjL/zji7DCUCvL5qp8Y0lDQNMydIQ1FjZ1VVYlqFQjw0jF7ZGv2Th/A7JGt+EfW5UXDfdya+wqHTNF2n+MvMnjc5Vtmn47lrssL+GPXPj7685TdsYqiKEr5HTqfxvkrBe1l9EbJnB+PYjBZfza/Tfu73efrhJE+mr20EqcJF6nXHE+USCIQx/YU5UgX1hi7k4YnRlkwk+ctsgkR9vu/5pMIS0/RHaZmVttT1hm78ptrD6QolFz2m85aXcl9uPMTVRMaPjYMshzPkG58Ziy5n/hs/R3F/k4EuIJ1Ml74+kaNG7QYAUCyd5MS71OY1juo2HMuGoG/Rwnt5LztJKpB11YEqypIKWOllBFSSlcpZaSU8iMp5UIp5cK88+9KKVtKKdtKKbtKKbc4O2al8kXENGHHvxXbt1hxjvzZ1PEdze/p4zv6su6XuArbq1qVVKJahbQawbjO9ejd1Fxo4piM4tbc2dyf+x/2mOz/cvMUOdzn8iO/uU2hweapkKw2uyuKolSkX49YL98UmPjx4AWbcaYSfmX20u5ngJ32ZOWhE0ZC04/aHE+LGcjvxtbEGduywdiercYWPKZ/jIsEINFwBS+r8c3E2RLvIz2DGdMlhi4xgeSgY2LuFH43tmaNsTuz9HdTv0lrxKhFUL8ndJ8M3R/noF8v/qcfxxZjC7abbPeDtmta3/Lz6wbzXs/fja15VD8ZQ53Oxcay2DCYL4z92WSyv18WbPfhzjOMYqmhD1uMLdjbdR545W2jbNS/xNddmM4nuNiVuiE+bmg0JSzjdbOzjC4gxuF7K0p1Y/Srx/nkquu1rFSO/NnUYG/zDs9gb5cKmVWNfWoO3WKncvR0ApF9JvDRyp8rItwSqT2qVUyrESwe34l98VdYsfssS3ecZaOpIxtzO1JPJDK/+VFi/vkCf2G97EsnjAzSb0S+2xmaD2HN1Wa8Ed+MpjHRvDW2HX4lfeurKIqiFCvuqDlRDSGVD3Vv0lCc5yPjYOYZbgcgSiTyvuvbtNacLvYaw7UVO+nUL2Od9YG+08jtMJnxL28o9jmXpTeBhfalPum6osR7aHzCeXVUGwAmL/2LtftgvP45y/k+TUOhdQdofbvlWKivOwsShrHAOIyemn3coLNeKti0fjSPhzfm7Y3HycaNGYYJALx+WxvGRF2GhbNs4ngidyLfmm4C4KSM4F9TKNGaJJtxqfhYPU7Dm+cMDwLwWUwXy/GG3YbDnmdKfO2WvwPPQAI9dVzKyLU5F+rjVvKT9XZaELnobI8pSg3RpNdIlmx6n6dvv8HZoSjXYNOOfZw7n8NXB85bHa+TvI8n7x9d7usufaP8hfLKSyWqTuCi1dAxOoB2Uf7cUD+IffGX8XFz4ZY2N9Es3JedRx9lw5LXmaBZZ7OMTCDh8HeM4Dv6Sg++OnEz7y8ZzLMP3IGo4QUcFEVRqtqVLD17z5qXyD7v+hXtNCcBmOKyil+N7dkvG/Kodk2JSWppEtwaEZH9j6Wfabl4mBOqklymjG0DCu2x7N00hLX7zlmd7tXUts1MSKE9m1elnX6hHgGEutomeD7uLhDYwG4YqVZxC341tWeCxvab/yvSy+ZYPk9dwRLlgBDH96jiEUCIj5vdRDWkpP2pAJ62+3oVpSYLCAln+yVVD6WmW/vBy84OocKopb9OpNUIRrSvy4yhLXlyQFOahZuXEXVuWo+xk19jfssVPKN/kFMmO/tgAF+RxSMu3/Fcwv9xYdFtcCWhKsNXFEWp8f65mI6U4IKBkdrNVufGaDcBMM5l0zXdQ+cXyklZhuTJHo8ANBpBuyj/YoccMdUr2zXD21h+7NM0FG+3gu+uuzcMItjbNuGs41eQvKVhL1ENtFuAyMfdFXReENbK5twxU5TV4zhTO7vhpkofu8cBPFytCzVtb/wf63tE3o5dATHUD7afAMcE2Xl9hXW63/pxMS1rFKUmca3TkqP/qlY1SvWgEtVqqkGIN6+M6cTU52YzRM5jUu5jJRaZiDi/Ed7rAnGvQmZKseMURVGUAqeTzdssOmts94R21Byz3waljLx8A/mthL2XAIZukznnXkIhnrzZu5dHtKJNpB8NQ7yoF2idSM013MbvxtYlB+PqZd5b2fQW6P6Y5XCAl443x7SlSZg33RsG8cpI+9eJKZTU2Z1R9QwkxM6SWR/3vCR46HwIa41B60GCDGKG/h7OYd2ic7upOZnS9hqpJcwYe+isE9VOo6eyJ2AQF0QIuyJiCer3mM1zTAho0JueTWxnjsH+jLKVuh2g93PgH20u5NTlwZLHK0oN0OymoSz5Q9VDqX4k1b32tjm+ig3SoURVCDFICHFUCHFCCPFsMWPGCCEOCSEOCiG+qtAoa7Egbzc+GN+F/f79uCX3FcblTuNTwwBypJ1V27np8Ntr5oT1zLaqD7aSDBkyhNati//wNWnSJAICAsjJcawlxIkTJxBC8OOPP1qORUZG8uyzdv/Xtti7dy9CCP7880/HAs+zcOFC1q5da3PckXtWFIPBgBCChQsXVsn9FKWmOJWXqPbW7LU511xzllPud13zPVw9/YqdJczn0nI4dR5dX/wAD3Oi2qquH2sn9WDjf3rz+9Q+LB7fyTLkIgGM1z9Hw+wvMGns1C24cwW8cA6eOwuxS22Wrg5sGc7PT/Tiqwe7WiWkhRWefbyKh504A+zu7bQkqpEdYeKfHJpwhBtz3uEz40CbsTno+MtOgcHmUaF2YwLrpb8AWp07HR7/mvAZJ+j08EI8wm0rASe5NwSvYEuBw6K61C9laa8Q0PtZmLIfxnwGHsXPditKTeHp7cPZDBdUR6LqRWvIJkdqq22yKiXkSC1aQ3bpg8ug1D2qQggt8B7QH4gHdgoh1kopDxUa0xh4DrhRSpkqhCj+t4lSZj0aB/PLkz15cfXfLN8l2GZqwWLjLQzVbGOYdjPNNUUqO2ZchE9ugY73woCav049NjaWu+66i4MHD9KyZUurc0ajkRUrVjBq1Cjc3EopfFGC7777juDg4NIHlsPChQvp1KkTw4YNq7J7KorimPxEtZdmf6Xdw8XTjx12KuRaqdMBkCA0IO3M4nrY7/cZ6mv7vmdEi9EvGk3qiSLXuPY9lYUT2CzsvOfqvO0uGS68rLjodezZJZtwIwetjgV4Ff8eX3Tpr815d9ukOtGnOeFAhJ/tucah3ri5lN73VVGuR/5Nu7Pl4ElubBXj7FCUPF7GFDLSIdvFHaiONWkkWsNVvIwVu6rTkWJKXYATUsqTAEKIZcBw4FChMQ8C70kpUwGklLbl+pRr4uai5X+3taFhiDev/XiEeBnKAuMwPjAO4Q7tRp52+Ro/kVnwBGmEXR+ZP/Q0uL/4C9cAw4cPx9PTk2XLlvHf//7X6lxcXByJiYnExsZe0z3at29/Tc+vKfdUSiaEGAS8DWiBxVLK14qcjwY+BkKAFOAuKWV8lQeqVJjTlzJwwUAjUUF7/Hs9A7/9z+qQcPejYUQQ65K7MkRrZ7VL+7tBk7fAySsE0u3sD/Oy/6VWTLAXrlqB3ljwNbuPmwva4EZQNFH1tJ/sloW3mwsaAeYWs4LDpqiCL0s9g8C3Djqthsah3hxPMlcgDvLSEehlXQjK173kSvVLDX2ZrPsOYTKYD9TvVWxP0yAvnXkPbAmEEKw2dmdEXnVmkxTsjhhH/oLsJ25uwtwNxyzjH+7VsMTrKcr1rEmXvqxcukklqtWIBomP8RLUslpXjiz9rQsUnrKLzztWWBOgiRBisxBiW96HPRtCiIeEELuEELsuXrxYvohrMSEED/dqyO9P92F+bHtiu0RhQsMSY3+657zDQsNQ2ycdWE61XSfgIG9vb4YMGcLXX39tc27ZsmWEhYXRp08fABISEpgwYQL169fHw8ODJk2aMGPGDPR6fYn3sLcM95133iEqKgovLy+GDx/OhQu2fRXnzJlDp06d8PX1JSwsjOHDh/PPP/9Yzvfo0YN9+/bx0UcfIYRACMGSJUuKveeyZcto1aoVbm5u1KtXj+nTp2M0FrwrLV68GCEEBw8e5Oabb8bLy4vmzZuzZs2aUv4W7Zs/fz6NGjXCzc2Nxo0bM3/+fKvzZ86c4fbbbyckJAQPDw8aNWrEzJkzLecPHDjAwIEDCQgIwNvbmxYtWtTY5cWFVo8MBloAsUKIFkWGvQF8LqVsA8wCXq3aKJWKJKXk1MUMosRFXIT1LGZJPVMtfOrA+LXQeCBoddB8KNz0H9txLm68cEtzPtTdxXEZhUnkfUescTEXNOrzfMFYbzvF83wjwdXOMlvMCd+zg5tbZhS9dFpeHNICTbCd/a7FzMqWlX+h6sOzDXdxUfqBmx8Mfh205oTxxSEtCPbW4ePuwvShLXDROlYSo1GoNzqthrH9uiIGzAZXT/Pr7ze92OR2+tAWaEvqd5rnbcNtHDRFkyY9eMMwmlTvxpZzD/VsQI9Gwei0Goa3q8Oo9kU/5ihK7eGqcyPF5I3eUMuyIqXacWRG1d67f9HMxwVoDPQGIoE/hBCtpJSXrZ4k5SJgEUCnTp1qdvbkRFGBnkQFeqLTCpbuMH+HkIEHrxli2WNqxCLd3ILB2VfAUGTv5ky/Koy2BDMdbyodGxvL8uXL2b17Nx07dgRAr9fz7bffcuedd6LVmj+kXbx4keDgYObNm4e/vz9HjhzhpZdeIjk5mffee8/h+61cuZLJkyfz6KOPMnToUOLi4njwQdtCGfHx8UyePJl69epx5coVFixYQI8ePTh27Bg+Pj4sWrSIESNG0Lx5c557ztyfsFEj+wVT1q9fT2xsLBMmTOCNN95g7969TJ8+nZSUFN59912bv4+HHnqIqVOnMm/ePMaOHcupU6eIiHC8suiCBQuYMmUK//nPf+jfvz8bN25kypQp5Obm8tRTTwFw1113YTQaWbx4Mb6+vpw8eZLjx81FFqSUDBkyhLZt2/LVV1+h0+k4cuQIaWlpDsdQzTiyeqQF8ETez3HA6iqNULlm5y5nMW/DMTJzjYzuFEV3w3Y+dHvLelB0DzR3fM2JZc/Q6NQS+xfyCoH/HDb/3KAXGA2gLeZXqiGHHo2D6fHi3RiNd6ARwjyDajKZ9zkWbi3mEw4XiixDDrLf1iXf/T3qM75bNBk5BrzdXMxJ4XY7FYDdKua939/TlZS8di5/mlrTOWcBp1+61WpMzyYh7JrWv8TrBHvrSE63bguz4clehR41MRco0pjf3zO37bO5xqlXb3G4NdspGcGtua+gxYQRLY8Xep6HTsuSB27AYDQ5nFQryvUsvEN/ftixmWHdS9m2oCiVyJFENR4oXDs+EjhnZ8w2KaUeOCWEOIo5cd1ZIVEqdrWqa/uh42dTZ7429GZs4XYK+kybcTXN4MGD8ff3Z9myZZZE9aeffiIlJcVq2W+7du1o166gaMmNN96Ih4cHjzzyCG+//TYuLo61Dp49ezZDhgyxJIgDBw4kMTGRTz/91Grc22+/bfnZaDTSv39/QkJC+O6777jjjjto0aIFnp6ehISE0LVr1xLvOX36dG6++WY+/vhjAAYNGoTJZGL69Om88MILVknoU089xfjx4y2vOTw8nO+//54HHnjAoddnMBh46aWXuP/++5kzZw4AAwYMIDU1ldmzZzN58mR0Oh07duzg22+/ZfDgwQCWmWuAxMREzpw5w48//kjz5s0B6Nevn0P3r6bsrR4p2vV8H3Ab5uXBIwEfIUSQlPJS1YSoXKuZaw/y8yHz0to9+w8Q5zbfdlBQA3DzJq3JKCguUS26j7S4JBWs3oPzv1QDCpb7FmZvRjWohGrAeVy1GquZTrv7Ue3drxwCPHVAxjVfJ9zP3SZRtaEp+PvKzLWd3Sl7/3CBEfM1NXaeq5JURTGr37oLP326SiWqilM58o68E2gshKgvhNAB44CiJUxXA30AhBDBmJcCn6zIQBVbdf09aBZu21fuB1Nn6wP6LPvFOWoQNzc3Ro4cyfLlyy2V6L7++muio6OtEkCTycSbb75J8+bN8fDwwNXVlXvuuYesrCzi4x3bSpibm8u+ffsYPny41fFRo0bZjN2yZQs333wzQUFBuLi44OXlRWZmJseOHbMZWxK9Xs/evXsZPXq01fGxY8diNBrZts16X9uAAQMsP4eGhhIcHOzw6wPzkt7ExES797t8+TIHD5qLmLRr145nnnmGzz77jLNnrYt2hYSEULduXR5++GGWL19OUlKN35ruyOqRp4BeQoi/gF5AAmCwuZDa5lAtGU3SkqQCDNLuxE3Y/OeDQPP+RJfI9lyQxSyX7VtCz8wmg60ftyqmh6c9PuHFxlMmDXpZP67byf64cni0j3U893QrvnVaSSb1sU7A7+9Rv8TxYztb91uN7VK2vrE3Nbbe5zuolZ2/a0VRANBoNGS6hZCe6VhHBUWpDKUmqlJKAzAJ+Ak4DCyXUh4UQswSQuSXMf0JuCSEOIR5OdzTaoah8gkhmDeuHTc3D2NgyzA+usf8QWSLqRVpstB+JmmE7Bq7HNMiNjaWM2fOsHXrVrKzs1mzZg2xsbFW36i/+eabPPPMM4wePZq1a9eyY8cOy77L7GzHSmYnJSVhMpkIDbUuXl308alTpxg4cCBarZZFixaxefNmdu7cSWBgoMP3KnxPo9FIWJj1bEr+45QU6ypq/v7WbRB0Ol2Z7nn+/Hmr6xd3vxUrVtCuXTsef/xx6tWrR4cOHYiLiwPMM0M///wzwcHBTJgwgYiICHr27Mm+fbbL82qIUlePSCnPSSlHSSnbAy/kHbNZwy6lXCSl7CSl7BQSUkovRqXKnLucZfU4WtjuOwcsM5j+nu68oL/PtqdnRDtodVvxN+rzXMHMaKvbIbyU3qaF2Z1RLUei6h0KPZ82/+zqZS7yVEF6Nwm1tHSp6+/B+O4x5brOgBbhVte584aSE89uDYIsPU/r+nvwcM+Sl0QX9WT/JgTlFXUa1zmKpna+6FUUpUBMt2Es/+Ows8NQajGH1kFKKdcD64scm17oZwk8mfdHqULNwn1ZfE/BN+WP9GrIwt/+Ya2xO3e5bLQcN2Uko8nv8VaGvaHVSd++fQkLC2PZsmWcP3+eq1ev2lT7/eabbxg3bhyzZs2yHNu/v2xtJ0JDQ9FoNDYzhEUf//DDD+Tk5LB69Wo8PMxfDOTm5nL5stXWbIfvqdVqbe6RmGie/QkMvPa2EoXlLyMu7X6RkZF8/vnnGI1GduzYwfTp0xk2bBhnz57F39+fFi1asGrVKnJzc/njjz+YOnUqQ4YM4cyZM+VYkud0ltUjmGdKxwF3FB6Qt2IkRUppwtyS6+Mqj1Ipt5PJ1stVw0Qx/1bzEkN/L1c2mjrSLmcRnmSTjgc/PdSChtH1S17qG9EWJv8FOenmhLEs/xbsJarlmVEF86xvl4fB1R3cKi4p02gEn9zbmcS0HPw9XXEvpTVMaddJupqDn0fp13HRavj03s5cTHdsfFHt6wXwxzN9yMgxEmKn16uiKNbqNGjK9l/TuM/ZgSi1ltqMcZ25pbV5KdNSY1+r4yL3qm1RpRpGq9UyevRovvnmG7766iuaN29OmzZtrMZkZWXZ9FP98ssvy3QfnU5HmzZtbCrprlq1yuZeWq3Wat/rsmXLMJmsl1k7Mtvp6upK+/bt+eabb6yOL1++HK1WW+r+1rKKjo4mLCzM7v0CAgJs+tVqtVq6devG9OnTSU9P58yZM1bndTod/fr1Y8qUKcTHx9fIgkoOrh7pDRwVQhwDwoDZTglWKZfTRRLVmOJmVAPMS1B98np/5uLKZXww4ILwiSg5Sc2n8wKfsLIlqQDuvnbiiSnbNQrzDqnQJDWfEIJwP/dyJ6mFrxPm6/h1NJqyjS/KU+eiklRFKQNTQDSJKTXvd7pyfXCssoxSY7SJ9Gd8t2g+3woHTDG01pwGzJvvZGYKwtfxqrDVUWxsLO+++y7ffvut1axpvv79+7NgwQI6depEgwYN+Pzzzzl9+nSZ7/P8888zZswYJk2axLBhw4iLi2PDhg1WY/r168fUqVOZMGECEyZM4MCBA8ydOxdfX+sPms2aNSMuLo6ff/6ZwMBAGjRoYHeG9KWXXuLWW2/lgQceYPTo0ezbt4+ZM2fyyCOPlKmaryO0Wi0zZszg0UcfJSAggH79+hEXF8eHH37I66+/jk6n49KlSwwdOpS7776bJk2akJWVxRtvvEGdOnVo2rQpe/bs4bnnnmPs2LHUr1+flJQU5syZQ8eOHfHzqyaVpcvIgdUjK4AVVR2XUjFOFUpUBSb7iWpQI/MMJPYL9VR6khPS3PqxRwC46OyPVRRFqWSNbxrJkk0L+c+oLs4ORamF1IzqdWjW8FasfvRGlhWZVTWmJyNNNbuoUrdu3YiJiUFKybhx42zOv/TSS4wZM4bnn3+e2NhYvLy8mDt3rp0rlWz06NHMmzePb7/9lhEjRnDgwAE+/PBDqzHt2rXjo48+YsuWLQwZMoTly5ezcuVKfHysZy+mT59OkyZNGD16NJ07d2b9eqs8yOKWW27hq6++Ytu2bQwdOpT58+czdepUq8rCFWnixInMnTuXFStWMGTIEL755hvmzp1raU3j6elJixYtmDdvHkOHDmXChAn4+vry888/4+bmRp06dQgJCeHll19m8ODBTJo0idatW7N6terYolRPhRPVCFJwF9b9laXQQs+pVsdeHtHKMik64cYYfIrp5VlhfMKg/V3mn4UWBqpWvYqiOE9AaASHkkruRa8olUXkV1Ctap06dZK7du1yyr1riwkLN/De+Tv4d9AXNI82FwJK96iLd0BoKc9UlMpz+PBhSzsbe4QQu6WUFVei1MnUe1310WtOHP9eygQkr7gs5g6XOMu5NOmB8eEtBNSxLdBz8mI62XoTLerYWZZbGaSE8/vMS3bLU0hJqRGut/e6Hw6cl/GpWaUPVGqcPT98yRNtc2lST31+VMrIzQc63lvuoiVqRvU6Nv32bvyiudHqmFtWItJk24tOURTleqY3msj/EH2ndqNVkgoQZ+qAX7j99igNQryrLkkF877WOu1UkqooSrXQrMdQlvx+3NlhKLWQSlSvY/WDvWg7biayUHtIVwzkXC6mgIiiKMp1KjEtG6PJvIKon2aP7XldFBpNjatUrSjlIoT4WAiRJIT4u5jzQggxXwhxQgixXwjRoapjVKoPTx9fzmZocdYqTKX2UonqdS6maVtytJ5Wx1yzL4GaVVUUpRbJyCl4z/MVmTbnf3PrXYXRKIrTfQoMKuH8YKBx3p+HgAVVEJNSjfk17ca2Q2dKH1hNJV9O57ZnF3LpSkbpg5VqQyWqtYGbL0ZZ8J9aixEyLzkxIEVRlKqVnmOw/OyF9T66B3Of5Jg+pKpDUhSnkVL+DqSUMGQ48Lk02wb4CyFqdtsA5Zo06dKPFdtOOzuMcvv8+y2kXjjLZ+s2OzsUpQxUe5paQKvVkizdCROF+mClJ4FXMAj1XYVSddSyIcVZMnMLJ6rWfY2PyigyCyWyiqJQFzhb6HF83rHzhQcJIR7CPOPKY9Nfp3W/26oswOrk1UmxpKdftTnu7e3Dc+8udUJE5VPa67hk8kZvMOLqcm39k6ta8uV01v22kwWjgpm4bif3DLmRID8vZ4elOEAlqrWAm07HRb0nIbqraEReomDSQ1YqeAY5NzilVsnKysLVtZLbeyiKHRmFZ1SFdaKaId0Z2rZOVYekKNWZvQ3bNt80SikXAYugdlf9TU+/SoMH3rE5fnLxY06IpvzyX8eFsycxGgu2S5xdNo0X7h2CFhM/tfZmSNemToyy7D7/fgtDGmloGurGkEbZfLZuM0/eOcDZYSkOUNNptUBEeBiJSUlc0Htaz2ilJzkvKKVWkVKSmZlJQkICoaGqvL1S9QrvUS06o5qj8eD+HvYr/ipKLRUPRBV6HAmcc1IsShUzGo24Bdez/HH1DqTBA+9gkIIf99esgpz5s6njO5hnUMd38GLdbzvVXtUaQs2o1gK+vr6sPZrO1YxMmrpfwdK9HiBJD1o1w6VUPldXV8LCwvD1rcI2H4qSJ3/prxYj7qKgeb0JDcv+rw+Nw3ycFZqiVEdrgUlCiGXADcAVKeX5Up6jgNVsZGpyEi/cOwSoecuA7RFCkKELJj0zB29PN2eH45D82dRgb3PKE+ztwpBGmhJnVZMvp/Pwa0tY9Nzdaomwk6lEtZbIFm5M+TmRL11nc6P2YMGJQa9B14nOC0xRFKUKpOfNqBadTdW4edMq0t8ZISmK0wghlgK9gWAhRDwwA3AFkFIuBNYDtwAngExggnMirXnyZyMBy0wkVM9lwEX3pKYmJ5Fw+jhGg77Y50R3G8bKzau4p3/bqgjxmm3ac4xzSTl8dcB6FWGdxGPFJqqFCy+pJcLOpRLVWiIywNyi5ldTO6tE1XjsJ7QqUVUU5TqXP6NaNFFFp74tV2ofKWVsKecl8GgVhaM4SdG9tfvfnYhbcD0yL5ws9jl1GzZj66Y07qmKACvA2jcnlWm8KrxUvahEtZaIDPAAIM7Unhf5suDE6T8hJx3cvJ0UmaIoSuXLb0/jKYomquq9T1GUa+Pt7WOZMU1NTsLVOxAArbtnSU+rdrTunpz7dAo5aRdx8w2xOl6Y0S+KpNSrhAY4Z8tEZS7NdaTwkloaXHVUMaVaIipvRvWkjOBfU0ExG61JD/E7nBWWoihKlcjMW/rrXaSHqppRVRTlWj337lJmf7qO2Z+uIyA4lDaTFtBm0gJaPvCms0Mrk5YPvEmbSQtw0bri7e5i+eNBLicXP4a3tzkxbXjTSL7cdNhpcVZWT1RHCi8lX05nwGPzSEo49HYMBgAAIABJREFUo3qyVgE1o1pLtKrrh1YjMJpgq6kF0ZqCtfpXj/2JT8O+ToxOURSlcmXk5s+o5lifcFNFlBRFUQrzCwpm9qfrij0fFFaH7UnF72OtTJW1NDf5cjoDJs8jtkVB4SU/dw0dA9J5f2UcL95nLoq1YOUmRFYKPZr5sO43tTS4sqlEtZYI93Nn2q3NeXvjcXblNGUcmyznsv7ZjPqopijK9Sy/j6rao6ooSmUqvAy46HFns1c8af+7E9G6e5Z59tc1ojnHzybROKpqW85VVk/Uz7/fwsXkS3y4w42vD+YCkJaRTVZWNkEJe3jxviEkX05n5S9befcWD6bHZdKnqU4VXKpkKlGtRSbcWJ8JN9bn4zUa+OsDy3G/lH1gNIBW/e+gKMr1KSM3v+pv0aW/ao+qoigVpzq3oClaPCm/lc6FZdOskmtHkuqmNw3jy/X/Y+adVZeo5s+mLh9jjm98By/GLL/2Wc386254pB4T12XyzZwpSCkZM/VtFgwJY+K6TC5dyWDByk30i9JzQ6QnQxqbyDDq1axqJVOZSS3UrEVbLu7xJUSkAeBmyoLEA1CnvZMjUxRFqRyWGdWiS3/VjKqiKLXIwcX/wZidaXO8rH1evXz82JeuRUqJEKLc8ZSlMFF5eqI6cl97s7SA1bH3volj1YatfDlMh6tGML6tjjErMujT1F/NqlYilajWQu2jA/ldNmOgKCiidPlwHP4qUVUU5TqVqWZUFUVRMGZnUufeeVbHcpLPkL5hfpmv5df4BrYfPkPXFtHljqcsPUvL0xO1tPu+vyKOuO37rGZpR3y1Ha1GsHKcr+XYTR9s4db6JoRw4dBF8/7ctmHwya40WqWW/f6KY1SiWgt56LSc8+sAVwsS1cyjcfj3e9KJUSmKolSedMuMapE9qqo1l6Io14Gi+0/zlXWmtCya3NCfFV9PL3eiWtbCSGXpiVrSTG3h+972xWY00oAQ5qQ02NuFENdsWodprWZu3chl7QkXNp0vnDq50KphcJl7tSqOcyhRFUIMAt4GtMBiKeVrRc7fC8wBEvIOvSulXFyBcSoVTNuwF+xdaHkceHEnGPWgdXViVIqiKJXj/9m77/A4qyvx4987RTOSRr1YtoqLLBdsMK5gejMlmB5aCiGJY5YEWEhbWH5L2AQWQkISFgg1LL2H4timY9PcbVywcZWLJFuSJauN6pT7+2NUpmpG0kgjWefzPH7Q+773fecKsDRnzr3nNEkxJSHEUax07y5MSZkB52sP7+q31zRbLFS5EnA6XZhMxh7f31+FkTqeHSpT6/26I61tVDW5mf1wKelJ8QCUVbWwvgyW7u3K3JqsNiZlS1A60MIGqkopI/AoMA8oBdYqpRZprbf5DX1Nay3/9YaIaTPmUvV1Mpnt+1StuhlHyQbMY06I8cyEECK63G5Nk6Nj6a9/oCoZVSHE0KeVIWBJL8D+R67r/NpmS6Kmag+tVQd8xhiNPQ8yO2RPO4cP1q/hwhMm9Og+78JIVXYny3bWUbt9dVQKE3WXqfV/3Ta34n/Oief+9Qm89eBtUhRpkDFEMGYOsFtrXay1bgNeBS7p32mJ/nZsXiobDMf6nDu48YMYzUYIIfpPs8PFbcbX2Wj5Gd8zfep7UQJVIcQwcccjr5CWmU3umCKfPzn543r9zMLj5/L+pkM9vs+7MNLz6+pobHGQrJqZd9Nfqa5r7PV8vJ/tydQaOosjBXvdSyaamT7SxOmj2nzGicEhkqW/uUCJ13EpECztdoVS6jRgJ3Cb1rokyBgxSBgMirqcuXCo6y+lLv48hjMSQoj+0VqygVtM7wS/KHtUhRDDSLT7vBoMBuzmDBqbW0mMt0R8X0dhpOc3llPfYOfhCyz8YkkTqda+LQEO18LG/3VfuMzKkWY3F443cIe0mhl0IglUg9Wc1n7H/wJe0Vq3KqX+DXgOOCvgQUotBBYCFBQU9HCqItrSppwNh/7ceTyqYRM4WsBsjeGshBAiutwl60JflD2qQohBYKCKIfVHYaWCuRfxzy/f4bp50yK+p2Ov519e+hDK1nPucUlcsfcAcZb4PvUmDdfCxv91Tz4mpfPe+eV10mpmkIkkUC0F8r2O84CD3gO01tVeh08Bfwz2IK31k8CTALNmzfIPdsUAyy+cStlHGeQqz3++ON0GpWth7KkxnpkQQkRR9Z7Q12TprxBiELDbGxi34OGA88Gyn8EYlCFg72nH+WjoLpC+/eGX+Wr5c1w3L/i9oSrwemc/q+vs/GR6HDe/18SZE+N6HTBG2sImmq1uRP+JJFBdCxQppcbiqep7DfA97wFKqZFa644F6hcD30Z1lqJfjM2y8S/3FK4wdi35bdm1DKsEqkKIo4ixtjj0RQlUhRBDTKigseKV/yQ1K8fnXO7osT16RqgMbneBtFIKZ0o+h2sayEoLXEIcqgJvR/YzxWqguKqRCZkm5he5aHQ5ep1VjbQqr1TvHRrCBqpaa6dS6ibgAzztaZ7RWm9VSv0eWKe1XgTcopS6GHACR4Dr+3HOIkriTAb22GZAc1eg6tj9GVb5IEkIcRSJq9vXzUVZ+iuEGFq6CxrvfXZxn5/RG0WnXsZLy5/i1stm+5zvrgJvR1bz8VV14Gwj2erZbTgqWTN/gkWW4YqIqv6itV6qtZ6gtS7UWt/bfu6u9iAVrfUdWuspWutpWusztdbb+3PSInrqc+b6HCce3git9hjNRgghoszlJN4euBwOAHMiJGYN7HyEEOIolJGTy9bKtoDz3VXgXfTgTax74W4mjc0jOSUZLElgSeJgq5WXt7SyfMPOgfwWxCAUydJfcRQbkVdI8Z4cxhnKATBoJxxYBUXnxHhmQggRBXUHPD/XvDQZbCToJjj7LikeJ4QQUWIcMYk9pYcpzPN8ALhjfwV/efkjPr1hFBBYgbeDLMMVoURnh7UYsibkJLHSPcXnnKt4eWwmI4QQ0Vbtuz91jXsiD0x5B+4shxP/LUaTEiK2lFLnK6V2KKV2K6VuD3L9eqXUYaXUxvY/C2Ixz+Gko22M/5/eto2JhUmnXcyLn+/qPL790TfJt7lYvM2zUs+7Aq8QkZCM6jA3vSCV3+spfJ9POs8d+eZjss67J4azEkKIKKne7XO4z52D2ZoIpsj7/QlxNFFKGYFHgXl4OjusVUot0lpv8xv6mtZaUl0DpKOAUUeRo9rD5WhloKaqkp/Pn4NBGUjJyOzXwHXr07+ipaqSO6+f73PeZkuKqP9qYnIqmxoMaK2prmtk2859/OVcCze/V8Pzmx2YjJ78mFTWFZGSQHWYy06yMnLaPNj2v53n0ht2QFsTxCXEcGZCCBEF9gqfw1KdRXyc/OoTw9ocYLfWuhhAKfUqcAngH6iKGOgocrT5kRsZdf3fOs+3Vh0gd0xRZ5Y1XNAYTrBntFRVkvv9+8jJH+dzvidFmpLHz2bt9lK+3PAtN5yUzoUzUthhr4PcmRKcih6T39aCG75zAvu3jmC08ryhM+LGfmATtvFzw9wpxNFFKXU+8BCeCudPa63v97teADwHpLaPuV1rvXTAJyoi52zxOWzEQqbZGKPJCDEo5AIlXselwAlBxl2hlDoN2AncprUuCTKm06GSvbismRhN8tayvwVrHxONZ9x5/fyAILWnJpx4Ls89dzvfbvT0R4XQe1ND9VeNtoF6HRF9skdVkGmzsNc83udc/d51MZqNELHhtRzuAuAY4Fql1DF+w/4f8LrWejqentJ/H9hZih7zC1RbiSMhTgJVMaypIOe03/G/gDFa6+OAj/F8QBf4IKUWKqXWKaXWbX3zQXa+dCdf/d/dbP1yKa3NTVGethgK4ixW1u4o5YJxikyb50OLUHtTvfur9qeBeh0RffKxlwCgMnES1HX9BXaVbYzhbISIiUiWw2kguf3rFODggM5Q9Jyz1eewFTPxEqiK4a0UyPc6zsPvZ5nWutrr8Cngj8EepLV+EngSgG3vamoP4Ha7WbN9H4ve/gMVzSbiRk2maO55JKVmRPWbEINXnb2Fp9Y28tpW33Y13ntTu+uvGk0D9Tqif0igKgBoypgCdV3H1upvYjcZIWIjkuVwdwMfKqVuBhKBoH2clFILgYUABQUFUZ+o6AH/jKqOI16W/orhbS1QpJQaC5ThWR3yPe8BSqmRWutD7YcXA99G+nCDwcCJx4zmxGNGA7DzQCX//OSv7KjXuJLzGXviBWTnjo7KNyIGp1/+/V2+ee4OHl54esgxvv1VW3hu8Vf9sod1oF5H9A8JVAUAhlHTwKuLQ5p9NzjbwBQXu0kJMbAiWQ53LfCs1vpBpdRc4AWl1FSttdvnJq8sw6xZs/yfIQaSw3/pr1mW/ophTWvtVErdBHyAZ6/9M1rrrUqp3wPrtNaLgFuUUhcDTuAIcH1vX29CQTZ3FGQDUHGknn+ueI4N7zfTEp9J3sxzyZ8wFaWC/fgdnjqKHDkbqtj/yHWd5w3KQGs/V/2NRpEmAIPRiN2cTlNLGwnWwPeRHVnOcHtY+2rH/gqeePMjPrsxr0evI3taBw8JVAUAWSNyKdMZ5CrPah+TdkLFFsidGeOZCTFgwi6HA34KnA+gtV6plLICmUDlgMxQ9JxfRrWFOFn6K4a99iJwS/3O3eX19R3AHdF+3RHpyfx8vud9RUNjC0vWLOXLFS9iNySTNfU0xk07EZPJHO2XHVKiUShpMLx2/gnzeevLf/GDc44LuNaR5Qy2hzWa2c7bH32T+YWAoxkwR/w63ntaJfsaWxKoCgDy0xPY5C4k1+i1LeXAaglUxXASdjkccAA4G3hWKTUZsAKHB3SWomeC7VGVpb9CxFxSopVrzpzKNWeCw+ni06/X88FLizniiielcCbjZ5+JNcEW62mKXsormsKXX7zID4JskFm+YScHK1t5eYvvZ7zR7K9aVWtn3da9FFs1r2+rICutGYNBhX2dvuxplUxs9EmgKgDIT0vgbfcEvmNc03lu88oPmHrCjZ1/sYU4mkW4HO5XwFNKqdvwLAu+XmstS3sHM2ezz2GrNpMgfVSFGFTMJiPnzS7ivNlFaK1Zv6OEd969l0NNJuJGTmD8iReQnJ4Z62mKHlBK4UjKparWTmaq7wcOix68qd9f//klK7jt9Ax+eVoKf/k88j6ufdnTKpnY6JP2NAKAlAQz28y+nThG1G1k1Z6qGM1IiIGntV6qtZ6gtS7UWt/bfu6u9iAVrfU2rfXJWutpWuvjtdYfxnbGIqwgGVXZoyrE4KWUYtakAu754Sn844YT+fUMF47PHmLdM3ey+s2/U1G6N9ZTFBEaf+plvLS8qw5XVa2dK25/nOq6xn593Y6s6HUzPFnN62YksviztWFft7f3ed/72OWZEd8jwpOPlUUnV/axNFfEEa885cRHqFqW79sBRVkxnpkQQvRSkD2qVln6K8SQUZiXxe1Xet6HHK5p4K0VL7Lhw0ZaLBmMmnEOBROnYTAMvbzLfTddi93eEHDeZkuK6T7VaMocmceaiq4WNQOVceztHti+7J2V6sL9QwJV0enGsyax8aXxzDV2tY2ML18PnBK7SQkhRF/4Z1S1ZFSFGKqy0pK44cIZADQ2t7J07Ud88dyr1KskMqecQuHxJ2EyD41uBXZ7A+MWPBxwPljV3aHMOGICxWVVJCdaB6yfaW/3wEZyX7B9qJ3Z1AsTuOL/Srjvwmz+TXq2RoUEqqLTmZOy+Xr0TCjtClStdcXd3CGEEIObdjT79B1qRfqoCnE0SIy3cOVpU7jyNHA6XSzftJn3X3mPaqcV29jpFM05m/jE/mvlIiIz8dRLePGDP2PT9oCM43UXntQvxYd6uwc2kvuCZYU7sqlLvrVT09jG4m125o83SVY1CiRQFT4sIyZ4mnS0S2raH7vJCCFEX/kt/XWbLFIgToijjMlk5JyZhZwzsxCtNRt3lfH2v+7jYKMB04jxFM79DqkZ2bGeZsSOpmXBtpQ01lS2Ur51DW9cnQx09TNtbGkbUsWHQlUEXr5hJwcONVPfYOfhCyzc/F4NyUk2CqJYxXi4kkBV+IgbMcHnOKO1JEYzEUKIKPBb+ms0W2M0ESHEQFBKMX1CHtMn5AGw71A1b3zxCGurnbiSRzF6zgWMHF0Y41l2bzAtC45G0FxW28rMLLfP3s8LxsEz76/gnR9m9WkpcE9awvS1fUyofaiLHryJv7z0IZSt58IZKeywR15lWHRPAlXhw5Y7yed4lKsMtAYlGQghxBDjdqHcjq5DrTDHWWI4ISHEQBszMoPffDcDgOq6Rt5e8Qpff2qn0ZTGyBnnMGby9CFZjGmgRBo0dxfQplrh1d1NfFHStfezvrGFBKOzz8WHelKgqS/FnDqyqa9f5VlO3pEV/tH8k9Fah7wme1T7RgJV4SMtOw+7tmJTnuVyNppxNVRgTM6J8cyEEKKH/Jb9tmIm3iK/9oQYrjJSEllwwXQAmlraeG/tp3z23GvUk0TGMSdROP2UPn2Y1ZPso82WFDRDarMlBX3GYNddQHvHI4v56pm7+cdPZ2I0GqiqtXPVbx/qc2AXailuX8cG011FYKDX1YJF9+Q3tvBhMZvYo0ZyDF19yurLviVNAlUhxFDjt+y3hTgS4uTXnhACEqxxXHHqMVxxKrhcbr7Yso2lr31IlcNKwujjKJozj4Sk5B49sydLdrtbNnvn9fN79LqhRHuv69anf4WrpQkAh/1I5zxttvBFq7KmncVHGzZw/uyiPrWB8daTljB9bR/TXUVgoFdVhkV48htbBKgw5XGMsytQbTq0g7TJZ8ZwRkII0QvBMqpS8VcI4cdoNHDG8eM44/hxaK3ZUnyIt5bezzeNBgxZhRSeeAFpWUPvA/to73V1tTQx6vq/AdBadYDcMUURP2/88Sez9PnFnD+7qNftY7x1txTXP1Pak7Gh9LaSsOgbCVRFgCPxBeD1AZy7cmfsJiOEEL3laPY5bNVm4qWHqhCiG0opjiscxXGFowA4UH6Ef658jHWVDpxJORTMPp+RY4pQ/Vi7o7tlwUOVwWikwZROc2tbVIK+x/65nJlpdlLjU4Dus7LRyuCKgRdRoKqUOh94CDACT2ut7w8x7rvAG8BsrfW6qM1SDKiGpEKfQNVyeHPsJiOEEL3lt/S3FTMJEqgKIXqgICed2y6bA0BNfRPvrHqTdcvqaTKnkjP9bMZMnoHBGN2fK4OpBY130OywH6G16gAAxl58z3knXMhbXy7h+2cf2+d5/XPZBqqrm3l3VynJiV3V3INlZaORwQ2lr5WERffCBqpKKSPwKDAPT4fNtUqpRVrrbX7jkoBbgNX9MVExcOwZx8HBruPU2m3gdoNUxRNCDCV+S39biJOlv0KIXktLTuDH507jx0BLq4MP13/OJy+8ST2JpE2ci3a7Yz3FqPMOmu+8fn7nct/ykmLK9u0CoKaqEqXdrL//agzKQEpGZuc93lng/KKpfPHFi3z/7OCvFWnQV1VrJz3ByGtXjebGxU288adbux3fn8t2Q1USlgA2OiKJPOYAu7XWxVrrNuBV4JIg4/4APAC0BLkmhhBzxliOaFvncZyrEap3xXBGQgjRC8H2qEpGVQgRBVaLmYtPmsRDC07j6R9P57KUHZhajrD1T1fx7d9+yO4nfk7x0zdT/PTNQ3rJbigulwtLZgGWzALMtnRm3PEGM29/jZSMTO59djG3/+15xuSO4OZ7/955j1IKR1Iu1XWNQZ/pHfR1x7cwkiHs+EhU1dq54vbHQ84t2HXvSsKLP1vrcy3S70V0L5Klv7lAiddxKXCC9wCl1HQgX2u9WCn16yjOT8RAVrKVLe5xnG70WvJbtgGyJsZuUkII0VP+gaqWpb9CiOgzGg2cetxYDr31X2it2ba3nH+uLqakQaHSxzJu7ndiMq9o73X1fl5NVSVmWzoARmtCwNi1772GqWILa5a+ylnX3th5fvypl/HSsn9wy6WzfcZH2j4mGoWRggnXYzXY9VCVhPvaCkd0iSRQDbZbXHdeVMoA/BW4PuyDlFoILAQoKCiIbIZiwGUlWfhaj+N0vALVgxvg+GtjNykhhOipIO1pZOmvEKI/KaWYMm4kU8aNBKDscC1vfvUk6ytacSTmkD/7PEaNm9jnYkyRtJ6J9l5X/2XAwSoKAzTUHmHH52/z6GW5/GLx28z5zjXYUtIAyByZz+ry1oB7Im0f0x+FkcIFlsGua61DBsx9bYUjukQSqJYC+V7HefjsYCQJmAosb/9LlwMsUkpd7F9QSWv9JPAkwKxZszRiUMpKsrDZXeh7snxLbCYjhBC9FWTpb05KfIwmI4QYjnKzUnnpgzVUNbTicrloevMVWh1ONAZs6Vnc/fSiXhVjinbrmWha+95rXFQE47PjuaioMSCrahoxkb0Hqxk7KgPoWZa0PwojhQssg10HggbMj76xjOVrNkU94ztcRRKorgWKlFJjgTLgGuB7HRe11nVA565ppdRy4NdS9XfoyrJZ2Kv9+oXVl8VmMkII0UtNjY14L0hrJY7TJmSGHC/EcBGum4NSygI8D8wEqoGrtdb7BnqeR4uqhlam/OxBn3Mup4MNj97Cty/cQa07kdSJJ/DOS8/Q1NQUcL93lhQ8GcvWqhIcTXWYE1L6ff494XY52fH52/zuas+8rp2Rwvde882qTjj1Yl786EH+69qTgJ5lSaNdGClckBzqepzVRlVNYMDsdK/numlx0gonSsIGqlprp1LqJuADPD/QntFab1VK/R5Yp7Ve1N+TFAMrLSGOKpXuc043VKC0hn7sGyaEENG062AV07yOrdYE8tIC91IJMZxE2M3hp0CN1nq8Uuoa4I/A1QM/26OX0WQmISGBvy04Hbfbzapte3j2YDGp0+ZhziwgeeLcziDUP0u69r3XGGtrpW7DUjJPic22rFD7X82uZi4qspCRaAYgI9HMRUX4ZFWTUtP5pl6htUYp1a/tY8IJFySHuk7u5KBzu/hXj/DylqqYfC9Ho4j6qGqtlwJL/c7dFWLsGX2floglg0FhTUyhqc1CgvLsI1CuVmiphfi0GM9OCCEis7e82idQzU4fXJkHIWKks5sDgFKqo5uDd6B6CXB3+9dvAo8opZTWWrZt9QODwcBJU8eQnprClHOvxl5ZyqEN/6K1qRFDUiYuR1vn2I79n3efmcivVn6EY8Z3+iWr2lB7hFf/9Buu/e2fOzOh3kLtf33itz/gtc0HeG1zqc95W/lXPst/Ewtn8fWuUmZMyO/X9jHhhAuSexpEx/J7ORpFFKiK4Scr2UrF4VTGqoqukw3lEqgKIYaMpka7z3F2mgSqQhBBNwfvMe0r6+qADKDKe5B3kcwnfncjC8+d3F9zHlZs2XkUZecB0FJfw9crX2f9M3fQFp/Nwao65o/XjEkzckmRYlE/ZVVDVe0N54YHXgxa6OlIZS333XRtZ4A78cTzeO3Nu5kxIT/YYwZMuMBSAs/YkkBVBJVls1B5OI2x+AWq2fJLSAgxNLj9iinFBWmhIMQw1G03hx6M8SmSybZ3NbUH+jw54ctgNOJua+Leq6dT39jM/NteoGismSfKmynKaKV15Qvs3vo5BqPnLX00erZ2V7U3Et0VevIOYpuPVPD6R2tRSpGZZGHNY7/o89zF0UUCVRFUVpKFSp3qe7KhPDaTEUKI3nD4tkCQQFUIIHw3B+8xpUopE5ACHBmY6R19MpMsbH3qV0HPh1Ox4SNG2xydlWZ/OjOBX56WQptTs2xPExP21NGQnMhJl/2U8TPPwBLf959z4ar29oV3ENt65BA16xejDIodGz7grhe/ZGx2EkUjbIwZmc7IjBSMRkOPnj/nxkepaghsfyOB8NAkgaoIyhOo+n16ZpdAVQgxhEhGVYhguu3m0G4R8CNgJfBd4FPZn9p7kQZI/gGty+VCNVTw9/k2/vzZWizxNg4f8d8vaWKksZFrsvex6O3fU9FsJm7UZIrmnkdSakaP59qRTe2uam+0WNJHkjPvZwDY924i57K7Kas8yJbyAzSt3EfLkW2Y3K38a8n7tLS2YVBgMhoxm02YTCZGpCaw9nHfpbnBKiwDfPzHhYz7wV8CzksAO7hJoCqCyrJZOBiQUa0IPlgIIQYZrTUGV4unVn07iwSqQkTazeEfwAtKqd14MqnXxG7Gw4d/wPSXlz6EsvV85/gUttfXhaw02+HEY0YDsKukkjc/+Svb6zTulHzGnngB2bmjI5pDRza1u6q9/cVssTAifywj8scCp3eeX7RsDZNveRi3s4222kpaa8tx1JazfdkL/OyZDcThwKIcxBs1DQ12qvduJSEtG2tyOsrg+SXgduugAWywTLcYPCRQFUFlJVnZ6J9RbTgUm8kIIUQPtTrdxOHwOWe2xMdoNkIMLuG6OWitW4ArB3peokt3/T211txw/4s8eccPyUhJDLi3KD+bO67OBqDiSD3/XPEcG95vpiU+k7yZ55I/YSoqRLvBXV9/xdeVLWGr9vaHYEWYAGoPe1b0GUxxWDPzsGZ6Ck3Vb/yAOdf9V+c4p6MN95L51DotVO7agbOhCtxODICztYkdy94iPiWdxNQs4tOysCb3POMsBpYEqiKorCQLlfhlVO2SURVCDA31LQ4stPmeNFljMxkhxLBXVWvvNrj0111/T4Ca8pLOXp/dGZGezM/nzwTA3tTK4tVL+XLFi9gNyWROOZXC4+diMpk7x9/wwIu9/RY7heqxarMlBQ1EO4QqwrT+/sha+JrMcRjNcSSPnxlwrWTth6Se8gPa6g5TW3uIw3t24qivorqmnp//YzUW5STe6GJsdhKF2YmMHZlBXnYqZpMxyCuJgSKBqghqYk4SlfhmVF31h5C/rkKIoaChxYnVL6MqgaoQIlaeX7Ii4uASQvf3zCr7ltZmO49dnsmNiz0Z1kgCXwBbgoVrzpzKNWeCw+li2cYNvP/SEo644kkpnMn42WdiTbCF7aEaTqgeq+DJmvYmiI0Gg8mMNWMU1oxRneea9qxj+o8O8rKkAAAgAElEQVR+D4DT6eBw5SG2l5fQvOEATVU7MLpasConZtqIN7gZm21j3Agb43LSyR+RJoFsP5NAVQSVEm8mNSsf6rxO1h8ElxOM8r+NEGJwa2hxSkZVCDEodCzj7UlwGap/Z8e+1YnZFuaPb4k48PVnNhk5d1YR584qQmvN+h0lvLvoXg42mthxoAJ32aZ+2ZfaXRB75/Xz+/z8UNlcpd1h7zWZzGSNKiBrVAFwcsB1l9NJ9eFydpWX0LRxH/bDOzC5WrAanJhxEq+cFGTZGD/CxricNPJHpBFnlvfMfSH/9kRIU8flc3hDMlmqHgCjuw0qt8HI42I8MyGE6F5Di4NE5Vv1F4stNpMRQgxrHct4+xpcdrdvNdKsajBKKWZNKmDWpAKqau1cdOsHnDPWyItvPonR1cSk0y9vL3AUGwZlCJmF9RcqEO4ukxspo8lE5sg8MkfmAXMDrrucTmqrKviwvISmzftoPLwLk6uFOJzEKQcW5WR0ZqInkB2ZTn52KpY4c+ALiU4SqIqQ5ozLYOO6IuYZ13edLF0jgaoQYlCoa3bw2toDJFvNXDkrH6OhqzhIQ4uTLPwC1bjev5ETQojeiGZw2d2+1d4EvqFe48pj4vjlaSlkJ9Vhd+4ia9uLbPiwkRZrBqNmnEPBxGkYDD3rb9oXKRmZ3Pvs4j49o7tMbrQYTSYycnLJyMkFTgy47nI6qa2u5OPyEho376exag9GRxMW5eoMZAsyOgLZNApGpA37QFYCVRHS7DHpPOP2DVTb9q0mbvaCGM5KCCE87Weue2YNm0pqAdhZYeeui47pvN7Q4iAxIFCVjKoQYmBFM7gMtW91VMXOqASqwYPqzbzxp7O4ISWRxuZWlq79iC+ee5V6lUTmlFMoPP4kTOa4Pr82dF+E6WhgNJnIGDGKjBGjgBMCrrtdLmqrK/jkUCn/+mY/9mV7MDmbiVNOzLoNq8FFfrpvIGu1HN2BrASqIqSsJAtVaceB/dXOc237VhGdH0dCCNF728sbOoNUgGe+2usXqDpJVM2+N0mgKoQYQFW1dh56fRlpiWZe3tLqc603wWWofavREi6oToy3cOVpU7jyNHA6XXy2eTPvvfIeVc54pl7yC1Iysvr0+gOR9RzMDEYj6dmjSM8eBcwJuO52u6mrquDT8jIWb9tL4/JijM4mzDjae8m6yE9PYHyOjbE5aYzOSSPeMrTftUugKrqVM+kknGsNmJRnE7qt8QA0VkFiZoxnJkT0KaXOBx4CjMDTWuv7/a7/FTiz/TAByNZa+/VxEgOh+HBjwDmtdWdvwPoWJ4n4vjGUPapCiIH0/JIVFKYZmD/vlKgtze1PPcnYmkxGzp5RyNkzCmlqaeOGf/yF0264byCnO+wYDAbSskeSlj0SmBVw3e12U1ddyfLyUpZs30/j5/swOBqxtGdkLcpFXnoC47JtFI5MZXROOgnWwR3ISqAqunXKMQVsX1PAVLWv85yr/BuMhWfEbE5C9AellBF4FJgHlAJrlVKLtNbbOsZorW/zGn8zMH3AJyoAKK9vCTjX7HCREOf5tdbY3IxFdbWncWPAIFV/hRADpDeVfmOttxnbBGscJ4+Op/xAMTkF4/o0h/tuujZomxqbLWnYZ1zDMRgMpGXlkJaVQ6hAtr6mii8PlfLBzn3Yv/AEsnE4idMO4pSDvPQECkckMS4nhTEjM2IeyEqgKro1c3Qa7xnymcq+znNVe7cwQgJVcfSZA+zWWhcDKKVeBS4BtoUYfy3wuwGam/Czryowo1rT5OgMVNuafN/oOE0JxCkVcI8QQvSHaFX6HSrOOi6fh7au73Ogarc3MG7BwwHng+1dFT1jMBhIzcgmNSMbmBFwXWtN3ZHDnkB2934av9qPamskDocnmMVBblo840bYKMzxZGRtCZZ+nbMEqqJbJqOB5pQiqPui81zLwVDv24UY0nKBEq/jUoJVOwCUUqOBscCnAzAvEcS+6iCBamMbuanxADibfQNVl2lwZzKEEEeP/mgjU1Vr54b7X+TJO344KDOzY0dlYP9ke6ynIfpAKRU2kK0/UsXKijI+Kt5H44r90GbHgoM45cnK5qRaGZ+TRGFOCmNyMrBZ+lYISwJVEZY7owjquo4N1TtjNxkh+k+wdJsOMfYa4E2ttSvog5RaCCwEKCgoiM7shI9ge1TrmruW+rpa6n2uaWlNI4QYIP3RRub5JSuoKS8Z8MxspAGy2WQkzh24JWMokWXH3VNKkZKR5SmadczxAde11jTUVrO6vIxPivdhX7mfFGs5f53Z+9eUQFWEZR11DBR3HafYi0MPFmLoKgXyvY7zgIMhxl4D/CLUg7TWTwJPAsyaNStUsCt6qcXh4mBdc8D5mqY2AFxuzY4D5eC1IklLxV8hxACJdhuZWO537UmAHO9VFyASwQLDmqpKykuKycnv2xLi3pBlx32jlCI5LZPktEyYPA0Am7VvoaYEqiKs7IJJtGoTFuUEINl1BJqOQEJ6jGcmRFStBYqUUmOBMjzB6Pf8BymlJgJpwMqBnZ7oUHKkCR0k/K9p8rxJ+tXrG0lUvp/sK8moCiEGSLTbyMRqv2tPA+Q42nyqr4cTLDDc/MiNuFxBFyuJYUgCVRHWuBGp7NUjmaS6tu/pwztQo+fGcFZCRJfW2qmUugn4AE97mme01luVUr8H1mmtF7UPvRZ4VetgoZIYCHuDFFICqGtqo7K+hXc2HmSewTdQNVqPjobxQojhpT/2u0aqpwHy6IwEaqsq2qvO9o7RmkD5q/+P1sxsn/M2m/wMH44kUBVhjUi28LXKY5JXnRn7vvUkSaAqjjJa66XAUr9zd/kd3z2QcxKBQgWqNU0OdlfaAUjEN1CNS0ju93kJIUS09cd+10j0JkCenJfM+yXFfQpUpyx4kOKnb+beZxf3+hnByP7ToUkCVRGWUopDiZOhqWulY9ueL+H06C5tEULERk1jGw6Xm+zkyPqM2lud7K60k2w1MTYzsdtlXhX1LcQZDaQlRq8XW7CKv+D5Pj7fVQUgS3+FEEeFaO93jVRvAuTJBdm8+dVOmHFSv82rt2T/6dAUUaCqlDofeAjPcrintdb3+13/NzyFRVyAHViotZYeJkeRmqw5sP+ZzuPE8tWgNUhfQiGGtPe2HOLW1zbS6nRzy9lF/HLehG7Hf7C1nFte+ZpWpxuA0ydk8cz1szEaAn8W/PWjnTz0yS7iTAb+etXxXHjcyKjMOVRG9a2vyzq/TvDLqNLHEvlCCBEL0d7vGqneBMijMlNoqd4S1XkMZCbUZksKGrjKsuPYCRuoKqWMwKPAPDxVMdcqpRb5BaIva60fbx9/MfAX4Px+mK+IETXqOBr2xZOkPJU2rW1H4PAOyJ4U45kJIfrizx/u6Aw6H/50Fz89ZSwp8eagY7XW/PeirZ3jAT7beZiNJTXMHO1bXK22qY1Hlu0GoM3p5qFPdkYtUN1X1RR2jM0vo4pkVIVAKZUOvAaMAfYBV2mta4KMcwEdEccBrfXFAzVH0TdVtXZ+/Ifn0Gieu+vHvd7H2psAWSmFhdaIx0cSGA5kJlSWAA8+kWRU5wC7tdbFAEqpV4FLgM5AVWvt3bAukdC9B8UQlZeezDr3BM40buo6uf9LCVSFGMK01uzx6keqNeyubAgIOjtsPVjPwbrAPnnldYFvTDaX1uFyd/0q2Flh71E1yFCa2pyU14fv1ReQUZX2NEIA3A58orW+Xyl1e/vxfwQZ16y1DmyUKAa955esoOrgfmpb9ID3XAWIN0TeokYCQxGOIYIxueBVRceTVc31H6SU+oVSag/wAHBLdKYnBou8tHhWuyf7ntz3VWwmI4TwobXuDArdbo3D1ZXxdLk1HQWKtda0eWVD65oD31A0tDhDvs7yHZVBzze1dd2jtabV6aIiSDBZ29SzHnvV9lbqvO5xu3VnsaRw0pTfOMmoCgGeRMNz7V8/B1waw7mIKKuqtfPup2u46zQTGfGatz9ZTXVd8K0S/SXB4MLp7NnPeiFCiSSjGuzj74CMqdb6UeBRpdT3gP8H/CjgQUotBBYCFBQU9GymIqby0xOCBKpfyj5VIWKsxeFi4Qvr+Xzn4c5zmbY47r3sWF5ctZ8vdlVxyvhMfnzyGH7z5maa2pzc+Z3J/HDuGCobAjOhwc51+HR78EC12eHpeVdW28zC59exu9LuszzY+9mRFFU6VNfM9c+sZUeFZ1/S3HEZLDh1LP/59hYq6sMvK/ue8RO+a/zc96RkVIUAGKG1PgSgtT6klMoOMc6qlFoHOIH7tdbvDNgMRa89v2QFp+e2MX2kicsnab4oG7ieqx2KRiZTdqiUEfljB+w1IyH7T4emSALVUiDf6zgPONjN+FeBx4Jd0Fo/CTwJMGvWLFkePITkpFjZylgatYVE1f5GsbESqndDZlFsJyfEMPb212U+QSpAlb2NG15Y33n85e4qvtxd1Xn8h8Xf8p1jR1IZJOg7HCJQPdLYxtcltUGvNbd5AtVHl+1m68H6oGMAKhtamJgT/k3B/yzd3hmkAqwsrmZlcXXY+wAyqON3pucCL1gkUBXDg1LqYyBYf5A7e/CYAq31QaXUOOBTpdQWrfWeIK/VmYB44nc3svDcyf5DxADpyKb+8RQXGQlmrpsWx7s7Gnn7k9Vhe65W1dq54f4XefKOH/a5N+sxuSlsKt096AJVWWY8NEUSqK4FipRSY4Ey4Brge94DlFJFWutd7YcXArsQRxWz0UBWShLrGydwmtGrotu+LyVQFSKG7nir5xUW21xuln5TTmKcMeBaZYj9n5/vPIwO8fFiU3ug+vLqA92+brDAOGBuTjfLQmRuI3GGYRMWFWT5siz9FcOE1vqcUNeUUhVKqZHt2dSRQNC/bFrrg+3/LFZKLQemAwGBqncCgm3vamq7/xkg+k9HNnVMmhGzQZGZqLhkojmirOrzS1ZQU14SlezrxIJs7Ft24anB2neSCR3ewgaqWmunUuom4AM87Wme0VpvVUr9HlintV4E3KSUOgdwADUEWfYrhr68tHhWNUz2C1S/gFk/jt2khBC9srq4mqm5KQHnD9uDB5Ohlv2CZ+mvDhXFeuluWXGHdfuOYG8NvU/W3ws/ncPDn+6m+HAjGYlxXN6yjaBFJ+PkTY0QwCI879Hub//nu/4DlFJpQJPWulUplQmcjKf+iBjElm/YycYdjfxjre+2CzcGXBtCt5SpqrWz+LO1PHZ5JjcuXhs2+xpOalIC7sYjvb7fXySZ0IFsYTMU5nE0iaiPqtZ6KbDU79xdXl//e5TnJQah/PQEVu07xvfkro/B2QomS2wmJYTolcWbD7F486GA85X1rXy6vYIH3t9BQpyRP1w6lUk5yXzmt7zYW3ObK6Ig9I/vb+e5Ffs4a3I291wyFYNB4XJrfrfoGz75thKtCVvRNw4H95r+wanGLXwdN4tTx53LqUVzwdEM7/4Cvvk8xI2SURUCT4D6ulLqp8AB4EoApdQs4N+01guAycATSik3nqKb9/u1JBSDUG/7rT6/ZAXzxxuYmG1h/vjo7Gm1MrDFlAayhc1QmMfRJKJAVQjwZFTf1oUc1slkqfZ9aK11sOdTmHhBbCcnxDDUsTc0mvZWNXLrqxupb6/++4fF2/j1uRODVgju0NTmovhwZJUly+tbeHn1AablpXD17AIWbz7Ii6siXy54kWElV5o8wegFjo9g6ztw3JWw+XX45p+hb5RAVQi01tXA2UHOrwMWtH+9Ajh2gKcmYqAjm/r6VZ4VJ9fNSOSq1/ueVbWo7j+47EvmMdi9NVWVbH36V0xZ8GDPJxtFddVVlO0L3P1YV10VZLSIhASqImKFWTZcGHnfNYcfmj7uurD1bQlUhYiBfdXRbztQ3djmc7yq+AgffVvhc87Yngnt0OJw9XgujyzbzdWzC3ipB0EqwO1mvzcxn/7BE6iWrQt9kzUFbCN69DpCCHG068imZto84UCmzcT88YY+Z1XT4g20NDViTQge7PYl8xjs3rJ9u6he/JfeTTaK3NqNJTOwq4lbB1bBF5GJpI+qEADMHJ0GwGLXXN8L25eCo/vlekKI6NtbNTD98V5cud/n+DvHjvQ5bmpzsq+Hcyk50kxTm5PiHt6Xpep8T9S2z606oM6LJ0BNzIYL/wKm8G1xhBBiOFm+YScvb2ll1qOVnX9e3tLK8g07+/TcybmpVJbui84kxbAmGVURsVGp8YxKsbK2biKVOpVs1d6qoq0B9nwCky6M7QSFOJpsehVWPw4tdZAxHi74I6SP8xniHahebvic600fkEQTlaTh1gayVQ1tmFniOoFHXJcSvC22hwE3vzC+w+nGzXzuOo5HXJfibv8s84eutzknbgOfuGbwuPsizp+Sw782dXUp+3J3Fct2+O5h/dN3j+P0CVnM+Z9PQr7mit3VmAyeOV1sWMH1pvdJo4E9ehRpV/yNd/ebeN4vSA7qjR/D/q98z920HjLHh79XCCGGqd7uaw3nmLx0Pi/eRcGEKf3yfDF8SKAqemTWmHQWbWphqWsO15s+7Lqw9W0JVIWIltoD8PYNXcdHij3Fgq5f7DOsI4uZpw7zl7jHO8+PxXep7mTDAfbqkSxxnxjyJc8yfM2vzG8CMMuwk+06nw/dsznfsIbbza92nnemTGJU6sk+9zpcgRV/x2fbyEqyYDaqoNcB3vumnPL6FgpVGQ+aH8OsXJ3zd2/+b5bn3O8zPp4QKze2vuV7rIyQNjrk9yqEEKL/FOZm0vBlkFUu/cRoNOKwHwlYOjzQLWyUdnPw2VuDnhe9I4Gq6JFZY9JYtOkgS1wn+gaqO96D5hqIT4vd5IQ4WpStDzxXug60BtWVFe2okHu82h32kZcav+w2UL3D9LLP8X+aXubDttncZ37a5/y1pk9xxC3o9rXijAYKs20opRiXaWNHRWDRDIBPt3sC6vmGVZ1BagdD2XrOPCObhz/t+t6um+iCCBKspBaA0RzBQCGEGD6qau3ccP+LPHnHD/tULCkcq8WMydHUb8/3l5M/jqbMbO59dnH4wf0oNStHqv5GmQSqokdmFHgC0XV6AuU6jRxV47nQZodPfg/z/xrD2QlxlLAH6VnqbIbWBrAmd57qqMSb1bEMvxsnG7ZioY1W4si0Wajy65daaPBtVTPGUEEcDtKU3ed8ftO3HDIbu32tfz+niGSrJ1D8zXkTuemVDbQ4Aj9RrmnyzP9M49eBD2mtY8ZIK9fOyefVtSXkpyVwwxR7ZIFqRmEEg4QQYnh5fskKaspLotKCJpx/LV7KomWrA87bbEnYbElBg7dIMqB9ube/Dea5DVUSqIoeGZ9tw6DArQ284JzHb8yvd11c938w66eQMzV2ExTiaNBQHvy8vcInUK1p8lTozY4gUE1Qrcw1bGWiKuWc+Er+3HgSq/Xkbu+ZY9gecM5kSSA+LnSg+rerj+fS6bmdx+ccM4KNd53LoboWnC438/7q2+c0kzqONxQHf1hDOfddfhx3zlYkrnkItfSNbufbKUP2pgohji59zYZ2tKJ57PJMblzc9xY04bS0OZh0y/+ilG9thOKnb+5T5jNc+5pYGsxzG6qk6q/oEavZyJgMzw+2p1wXssftXf1Tw7p/xGZiQhxN7BXBz/sFsLXtGclIAlWAZ+P+xB3mV5jd8AnPxD1ABnXdjj/TsDHgnKorIcEYvH+rxWTgvCk5AeetZiNjMxMpzLJhNPi+aTnNsCn0BOyV4HZhe+Ma1JYIg1SAdMmoCiGOLt7Z0HCqau1ccfvjVNd1FdzraEUzMdvS2YKmPxmNBpyNkf1uEiIUCVRFjxWNsAHQhpk/Oa/2vbjuGbAfDnKXECJi3WVU2zldbhpanABk0fM3A4mqlfOMnt6jp0/ICjpmqmFv4EntxmovCTp+ztj0brOtBoMi0+bbJubYYK/RwV4OVTuhvjT0mGCyu88UCyHEUOKdDV382VqfANR7TEdw6h/Udtx/3QxPouG6GYkhnxMtcSYTLVU9/NkthB8JVEWPTRzRtdb+Y/cMGswZvgP+PJ5v1n2OEKKXIsio1rbvT4XIM6r+CtVBEuKM3Hnu2KDXJ6sDQc8ba4qxmAJ/fRSkJ4R9zewkq8/xGBUiKAdoqAjeH7U7o0+G0Sf17B4hhBjEIsmGdgSnf39zWUBQ23F/ps2z4y/TZur3rKrZbKKtOviHmkJESvaoih4r8gpUnZh4z3QWVzl8l+Udefc/+VP10/zmvEkDPb2jgtPlpqKhlUxbHBZT94VrxFEoZEa1vPO6+uJpfmSs5A3X6WR3FDXroZ+a3uOHl1xGXGLwT9WTVYiqjdW7SYibyAz3Fk43bOIz9zRWuqd0BaHFn8Huj6FoHow9zefW7CSLz3G3gaq93FNEylvGeLj8Kcg5Dqp3e9rQtDVCxTdgSfacN8jfGSHE0aEjG/r6VZ73XtfNSOSq1333mHpnXK9+eSVXTE1oD2pbeG7xVyzfsJODla28vMW3UN+oip39VlTJZDLhqAvxoasQEZJAVfTYhBG+1cv+VHMml9reJ87Z1YLiBMO3LFy2jV+fOzFgI73onr3VyfeeWsXm0jqKsm28tOAEspOt4W8URweXA5qqgl+zV4LbDa/9gIzStfy3GY4zFJPuV5m3J+LeXQjHf79nN1XvYYbRzBPm+zApNwv0Uq5ou5vs5GOhdD28cCloN6x8FBZ8BLkzO2/NTu4KVE04yVfdbBVoqIBGv+uzfgK5M9of1v5BmDkexp3Rs+9BCCGGgO6yoR1BZseYcelmzs53eH6P0BXUvvGnW3tUOCkabWyykq1sX/8eTcUbfM5LBVzRE7L0V/TY2MxE4r3aUxwmlZMa/+QzxqKczDbs6Cz2IiL36poDbC71FLnZVWnnpdXBl1+Ko1Sw1jQdGsrh4NdQurbz1BXGL7p93LuuCJbBbnwp0tl5lKzhWr0Ek/K0nDEpNz8xve/Jlq76uydIBdAuWPWYz61ZXkt/89ThzmcEZS+Har+KwFIoSQgxjCzfsJOXt7Qy69HKzj8vb2ll+YadgO/+0+o6Oz+ZHsey3Y1UN7oiWuIbqvBSpIWbQlnz2C+4/vJzuffZxT5/pDKu6AnJqIoeizMZuG1eEf+ztKt1RZVO5gPr+ZzX8n7nuZMN31DR0EJaYlywx4gQHvp4l+/xJ7u4bd6EAXv9rQfreHHVfsZmJvKTk8diMsrnWQMq1P7Ujmu7PuzR49a6J5KfmcKMmvf6ODEvlVs5x+/UJcYVbEk0wzdv+l7Y8gZc9iQYPP8feS/9Heu/7NcU77vUt6EiMLssrWeEEMPIogdv6va6d8Z1V00LSsG0ETD74VLSk+KB7pf4+vdWjWYbG6vBidvlwmCU7RiidyRQFb2y8DRPVsM7WH23fgLnxXUFqqcbNlFR38qkwG4VohvNjuCtPwaCvdXJdx9b2TkHlxtuPEMyWAOqm0C1rXo/TatfJLUHj6vUqbyZdz0zLrkZavbCu7/o+xxDGL/qP4Jf+OA/wZoCwImH7dxqOgjAVOVX8Xf0SbDnk67jmr3Q5rWsWRk9e1KFEEIABNl/agJMTC3MDBvkBgtKfQs3tfgsMe6p8SNsVFceJHNkfq/uF0ICVdFrC04ZxxvrStlV6XkjucI9BbdWGJQGYLKhhIP7VsCES2I5zSGjprGNP76/Hadbx2wOb64r8QmU//j+dglUB1qoQkpAnLuZuJaelfuv0zbStAHGnOz588Gd0NKLKsFjToV93S8zjt/2evALq7uW/44Hbg31m6dgrm+g2ua39za1AIzm8HMVQohhIlww2h3/oPTRN5axfM2mbgs39cQxeam8XbJHAlXRa7KmT/SawaD40UljOo9rSWK5e5rPmKJv/w46doHXUPKHxdt4dW1gKXerOfK/pi0OFy+s2s/r60pw9SLgLa9v7fE9IsrqD0b1cQdJZ3qBVw52zsLePWhu/2ViO404BhKzQ1/PLOr/OQghxFHIfy9qsN6qr3ywggvGqai1sZmYn0VD2a7wAwfAfTddy53Xzw/4c99N18Z6aqIbEqiKPpl3zAif4ydd832OC2pWwbL/AfthTwsJEdJbX5cFPd+T9jQ3vLCe/3rnG3775mbuevebiO+rbWqjvM6zt0XE2BHfvqE12hbxra3axKeu4zuPv3JNocVWwKXTc7sGTf8BGHu4b3z0KTDhfBg/r2f39YRthKdy77FXhh5z3NX99/pCCHEU8y+Q5F9NGKC6rpHHV9WFLNzUU5mpNhz13RQIHCD33XQtJfv2YDnnFp8/Cefdht3eEP4BImZk6a/okxHJVqblp7KpxLOUcJV7MhvdhRxv8Hqz/fkDnj/x6XDtK1BwYo9e40hjG6U1TUzMSRqWPUUjyaiu31/D62tL+GxnVyuPl1Yf4N7Ljg1770fbKrjlla9jujdWeKne7XN4o+NWMqinyNC15NelDaxxTyZBtTCt/e/auccVsDftZDLGzYC2lRSXHGR/4pm8N200Vq8q3aSNhpvWevqcjpoBVTvhSPteUWsy5M3xVBVu8VSeJmmEJ3hUCq78P9i+BI7s5akvijnQmsB69wRmGnaSoeq59ez2ol+JmZB/ApSshsbAVjsOl5udFQ3EmQwUZtkwxKfAMZdCXCKc+wdP+5kqr0/hDUbP88ad3vd/v0IIMcwE24vqv7f1SEMzeckG3JYE1r3wu6i8rlIKK21ReVZf2O0NmG3pWDILOs8521ppO1JGTVUld17flWSx2ZKkMvEgIoGq6LN5k7M7A1VQ3O74Ga/H/Z5k1eQ7sPkIPHMe/PsmSBsT0bO/PVTPtU+torbJwZRRybz185OGXbDqE2QEsbOigaueWNmrpb4Ad7y1ObpBqtaw4TnY8b4nsJhzQ2fFVxGG1gHtWPa4R7KKYyBYFxcNy9zTATj7pFO4MC+l/cJFjJsM40K9TtoYmL3A83VHT1Jv+bOD32dJgmnXAPC3Ze/T6PL8f7PNNQaAW8+80Hf8yOOCPsYMTAk1N4MRjjdzjzAAACAASURBVP1uqKsh1dfXU1lZicMhLbFEbJnNZrKzs0lOTo71VAIopa4E7gYmA3O01utCjDsfeAgwAk9rre8fsEmKqAtWIMl7b2tVrZ2rfvsQj81P4MbFTVTXNfa60q8/ixqcP5M1oAwmzLZ0xi14uPN88dM3x25SIoAEqqLPxmf7Nm/ergu4wXEbr8TdG/yGh6bBab+Fs+4M++w/vr+9vRerxnRoAzvf/pxjp06DSRfivU51b1UjD364A7PRwK/Pm0huanxfvqVBxRomMH/q8+JeB6kAVfbIP+3UWrOptI54s5GJOSGadu//Cv71756vd74HaWNh4vm9nt+w0ngY2rqWIdm1lcMR1vhNTRjYIkNzCzP4+NuuJV0zCnpSizi66uvrqaioIDc3l/j4eJSsYRcxorWmubmZsjLPVo5BGKx+A1wOPBFqgFLKCDwKzANKgbVKqUVa620DM0URTR3Z1O4KJEWz0q+/pDiNo7UVs8USfrAQfiTNIfpsZIo14NxK9xQ+dk0PfdPnD0Dl9sDz9sPwzT+h1lNUaPmOw5hx8pz5j7xruYtjtz4Ar30f1jzlc9vPX9rA4s2HePvrMn775qY+fT8DbV9VI/ct/TbkdUuYpb+r9laHvOZ0BUvD9d7di7Zy6aNfcd7fPufpL4qDD/rA7wOIJb+K6hz6k1LqfKXUDqXUbqXU7SHGXKWU2qaU2qqUejmqE/Bb9rtfjwAiC7qykgb2TcDNZxX57Gm+++KQOdJ+V1lZSW5uLgkJCRKkiphSSpGQkEBubi6VlbHfm+dPa/2t1npHmGFzgN1a62KtdRvwKiDl+4co/72o/gWSghVVWvzZ2s6iS301aWQylWX7ovIsMfxElFENtwREKfVLYAHgBA4DP9Fa74/yXMUglRMkUAV4wHkNcww7ApcAt3v+iQfYOOEW7rlsKglxJrBXwt/nQlMVmKywcDkAFxlWcLpxs+/NG1+EEzzVSxtaHHx7qL7z0le7q9FaD4k3rC0OF5f9/StqmkIvjQn3XaTGx1FCc9BrDpemryulO/5d1ja18dzKrr/W9yz5lgWnBllcWuVXdKG+Z+1UYiWSLIJSqgi4AzhZa12jlOqmRG0vVPsWUtqrI2tCnGQ1hV0iHm3T8lN5acEJfLGrilOLMjkuL3YZVYfDQXz80bOKQgx98fHxQ3kZei7gXYK+FDgh2ECl1EJgIcATv7uRhedO7v/ZiR4J7LPqMapiJ7/8/rndBrLRyKpOyU9nddkecsdN7POz+sJoTeDgs7d2HjudDtzNDcRn5cVwViKcsIFqhEtAvgZmaa2blFI3Ag8AUp5xmMi0WTAaVMDy0506nyva7uYkw1aSMnL4tf1BcDs7r1/n+idNW1pZkvMrrjzyFGzySk45W+DLvwKXcKIhSLbx8E5wu8FgoM0ZmDWsb3GSEj/w/Ra/PVTP5zsPM2dsOtML0sKOf2NdSbdBKkCbq/tlvd19n21ON/FxoQOYSDKubS43FpOR/dXBP3AIMHTbEXVmEQCUUh1ZBO+fdT8DHtVa1wBoraObMvHLqO6LMFDNHuBsaoeTCjM5qTAzJq/tbyh8MCWGj1j+/6iU+hgI9sPjTq31u5E8Isi5oD/YtdZPAk8CsO1dTe2BSKcpBki4PqvhAtm+KsrPwr42ti1qbLYksDeAtSvsqak6QnxWHlMWPBjDmYlwIsmohn3zprVe5jV+FfCDaE5SDG5GgyI7ycKhupaAa7t0HrtcecRVG7jpjj1Y/zYJnF3Zv38zLYZli4M/ePNrmLiQGYYgP+CczVC7D9LH0RokUK1taotqoLpyTzX3v/ctZqOB3100hWM7i9Z4aK3560c7eXjZbrT2/Dt5/Ya5zBzdfbC67VD4suiOMMFkQjeBaFs397Y6XXy8LXyc1dLmCVRrmwMDaqfLjcnovzR5yAaqkWQRJgAopb7Cs8Lkbq31+1GbQcVWn8O97pER3TbQy36FEIOX1vqcPj6iFMj3Os4DotvgWQwa4QLZvkqMt6Ba6sMP7EfBqvjed9O12O0NAcWTbLYQ9TdETEQSqEa8BKTdT4H3+jIpMfTkpFiDBqod2lxutla7mTl5Pmx5I+LnzjOsZ7whxO/HwztCBqo1TQ5GZ3idaKmDf90KB7+G6d+H034T8RzanG5ue20j5fWe7++Otzez+OZTfca8sqaE//20Kxvmcmve/+ZQ2EC1oSX80jCfjHFjlad1SO5MsGVT2dDCjorQwW6oQNXt1nz3sZVsKasL+/otThcpmKmoD/zv2+RwkRwQqA5ZkWQRTEARcAaeN29fKKWmaq1rvQd5L4crKCggIo5m2Pelz6lv9JiIbs1OCr78XgwNkWTfli1bxhlnnNGn18nJyWHBggXcc889fXqOt//4j//ggQce4J577uHOO8MXyBNDwlqgSCk1FigDrgG+F9spiaHMOggr/0oLmqEhkkA14iUgSqkfALOAoM3uevXmTQwJOcmBb5TPmzKCD7ZWdB6v31/DzHP+m9bN70Rcrvy3pldDX6z8FiZeQKszsLVKbZNfJdtVj8PWtzxff3oPjDsL8mZGNIfNpbWdQSrAN2X1VNtbybB1ZbFW7AnsFVlR3xr22fUtzrBjOjOqDeXw+KnQWAnmRD476y1+tqQm6NLnzntDXFu2ozKiIBU8+2gBKoJ8ENHU6iLZ6pe5HrpLfyPJIpQCq7TWDmCvUmoHnsB1rfcg7+Vws2bNiuxfyL7/3959h0dVpQ8c/54p6b3SQhdIQAQERAELoSkIgiLEQhEsK6yua/kpsoi6Rdd17WtZrAsmgBhACYoiig0UFaQoiID0GkBC6syc3x8zSaYmE1Im5f08Tx7m3nvuvefMJIf7zmlfuPQ2OKDj2KZTPJLFhQeRe8b19ztQXX9Fzfj666/LXhcUFDBo0CBmzZrFiBHly/2kpaVV+z45OTkkJdXcsGqtNQsWLAAgMzNTAtUGQCk1BngOSASWK6U2aK2HKaVaYJ+D5AqttUUpNQP4EHvPkde01lsquKwQFQqqB2upiobJn6YQv7qAKKUGAw8Co7TWXp/QtdavaK17a617JyYmnk1+RT3lrZvtBe3iXbb/nvMzr24qpkvR6/zqZ5fGdobDvg/uWQtAYYl7MKZJ+uE5e1D3wQNgKYJP/+6aZP1rft0f7N1+3W054NqNxVvAeSzPj0DVS3dad2WB6Nal9iAVoOQM1o/mVBikgu8W1a+8lMmX0jVWD3lrUS32Fmg32EC1rBVBKRWEvRVhmVuaJcBlAEqpBOxdgX1Mf1xFv6x02Vxt7Ym37wnPSYrw2JcUJYFqQ9avX7+ynz597GvYdujQwWW/r2VOCgt992Rx16tXL1q1qrmJQ7766it+++030tPT2bJlC5s2baqxa4vaobXO1lq30loHa62TtdbDHPsPaK2vcEqXo7XupLXuoLX2sdacEP5JCjdx5rR/X44L4cyfQLXShzelVE/sa3KNqvHJRUSDEBbk2Tjf0csD9aPvb0Vj4AlLDcy19cuHsPofFJW4tqhebPiRtJ+fhUM/wtr/wI8LPM896f+k1F/v9AzqNh9wrXDzHF14+6ifecA0n8sMP3Dcj/VJ/QpUS4PNH/7nsn+Q7Wsvqd3O9RHIuk6ipOmpfmGw4TtMeAaeJ87Y8+ithTi/2LM1u6HSWluA0laEn4CFWustSqlHlFKjHMk+BI4rpbYCq4F7tdb+R/2+bw7bP3TZ9Ymth9ek3tavla6/TcNLL72EUorvv/+egQMHEhoaynPPPYfWmrvvvptu3boRHh5OSkoKkyZN4ujRoy7nN2vWjFmzZpVtT5gwgQEDBpCTk0PXrl2JiIjgkksuYdu2ylYvscvMzCQ8PJzXX38ds9lMZqZnVzqLxcKjjz5Kx44dCQ4OJiUlhVtuucUlzaJFi+jduzehoaEkJCQwcuTIsnVIhRANX9eUGA7v3RXobIgGqNJA1c+HtyeACGCRUmqDUsq9FUI0ct4m9GmXEO4z/ce2Xmy0lS9tclqHssByKU+VXM1RHe3zPA+fPUbkzhyXXXeZFrumWeFlOcziM/BzDvzyUYVdVYssVr777YTH/i37XVtU84osdFJ7WRD0KLealvN60BO0O/2tx3nufq/KGNVoz26g0eRVeK6viZhKnGZonmRcSXbwQ8wNepIXzU97pM3471r+nvMTB056LoHjNVBtuF1/vbYiaK1na62XOV5rrfWftdZpWutztdYV9E2vgmO/uHx5UoSZr2ye65IGmQx0a+H59yFdf5uW8ePHc/XVV5OTk8PQoUOx2Wzk5uYya9YscnJyePLJJ9m6dStDhw5FV/L3uGPHDmbNmsWcOXOYN28ee/fuJSMjo9I8WK1WFi1axKhRo0hJSWHIkCFeA9XJkyfz17/+lRtuuIHly5fzz3/+k9Ony8fVz507l2uvvZa0tDQWLVrEq6++Srt27Th+vPrf/wgh6ofUlHh+3x/YmX9Fw+TXOqpa6xwgx23fbKfX1Z1hTjRwPVJc11AMMRtoERNKkNHgtfupBRPXFs9moGET+QSzwdaRfOytQoUE8YDZ84Hnz8W3MTXia7oWb3TZf843DxLL40SrMzxlfpGeBtclPijxsmj1ge8hy/EwduEMGOa9Z9PWA78zgyxuD17KbzqZW0r+zA7dyqNF9XShhTuNKzCo8ofCGyzvYrHehcloX0Jn74l8WkSHuiwX83tBFcao2jzT9jX8zEe23j7PraxF1YiVv5jKW2qHGL+njeUQv7kti/LKGu+9W8+4d/212cDmJfi2FIFJgimfQqJh8BzYvhL2rmOdNY0CPFtJ+7WPJ9nLusXS9ddV2/uXBzoLAOx+bETlic7CPffcw6233uqy7/XXXy97bbVaOf/88+nYsSPffvstffv29Xmt3Nxc1q1bR5s2bQB7V+KMjAx2795N27ZtfZ63atUqjhw5woQJEwB76+zEiRNZu3Yt/fr1A2Djxo3Mnz+fl19+2aUVtTQQLikpYebMmWRkZPDWW2+VHR89erSf74QQoiFo2zyeM6v866khhLNGM12nCKzLuiS5dPWdc2VXjAZFSlyoz3OKCOJj2/l8ZetWFqQCrLF190j7qfU83rUN5B9RM6HXRJdj5uJTjDF+yb+9Ban++PZVsHoPGM8c2MYfTUswKk17wyH+aFoCwG/H8znl1G03r9DCGKPrjK0DDJs5kV/C6cISRj3/BelPfsawp9dw8JS9ZfJMkaXC5WNK2bQjsDzjOWHTBd7WmHVS4mMNVotjfx/DNkzKNQ+pyv918E7ll/Dr0Tz7hEu/H4QFPlamKqp8GZ4mLTIZBtwFN62g5O4d/KVkktdkgzonEhvmOR48Ubr+NinOkyyVWrZsGf369SM6OhqTyUTHjh0B2L59e4XX6tSpU1mQCuWTNu3bt6/C8zIzM4mJiWH48OEAXHXVVYSGhrq0qn7yyScYDAYmTpzo9RqbN2/m6NGjTJkypcJ7CSEaNrPJSJDN//H0QpSSQFXUCKNBkX37RTx+9bnMn3YBE/raZ3WuqPuvLz/p1vxkK+/m+pstiTtLpgOKY5YwGPUcXOLanXe2+X/0OpsgFewzrR73fm70Ltc1Xkcbvyp7vTc3H7Av9ZJXbMHgZRKhyNcG8OnHy/n5kD1Q25Obz7y19i6e/ky2VKrEqr0GqucaKh7zUWx17Zr769E8fthzoqzL7hDDdx7nnKMqfkB19qcFG0h/8jOGP72GwvfugW0+WrKKAruGWkOSb4j0aNEudVmXJELNnt3so0L86hwjGonk5GSX7S+//JIxY8bQoUMH5s2bx9dff82aNWuAyidbiolx7Q0TFBRU6XlFRUVkZ2dz+eWXk5+fz8mTJ7FaraSnp7Nw4UKsjnrn+PHjxMbGEhLi/YuU0u69zZv7N7meEKLhCvY+z6oQFZKnG1FjIkPMjO/juuxQ2/iqB6qg+EPJn/ijaQkl2shTlms4hb21tmzN1B4Z8Nlj1cyxk8ObIamLx25roecYUIUNjYEjpwuBaPJLrETqPMzKc7xmyIntdFg/ByjvWvzC6l8ZmtbMrTVV01odoVibOES8+2UottoIzfcMVNuqQxUWq9hSHjwvXL+X+xf/SOnw1AjyucqtFRigs2EfVHGOpD3H8wg5877P439991tmTWvv87go59Gd2iGteRRt4sMpsdqIDw/iuGOJmj5tY/1ah1M0Hu6f9+LFi2ndujXz588v2+fvhEhnIycnh1OnTpGZmel1XOqnn35Keno68fHxnDhxgsLCQq/Bany8va47ePAg3bp1q7X8CiECL4hitNby/5WoEglURa2KDQ86q/N26+bcXfIHj/0FpZP3xLaFZt3tM/vWhEOb4NxrPHbrAs/p1BM5xRFiOeKYBfd0YQmpaq/PS6exixCKKKR8HOHoF74krXn5chP3mBYyw7QUgEWWi3nYMpE8wsqOFxechpJ8j2snq5OEUuh1PCO4Lk8z9/OdOM2hxJPml4hXnl1yq9KiOszwDUOM33NQx1WYrujMSb+v2dSdKfIMVLu2iOKxsfYu8WajgX9e052/Lf+JsGAjD13pOelSU1dbY0Prq4KCgrKW0FLOQWtNy8zMJDk5mawsz7nExo4dS2ZmJunp6aSnp2Oz2Zg3bx7Tpk3zSHvuueeSlJTEm2++yZAhQ2otv0KIwGubEM7Jo4eITZIeFMJ/EqiKWtXFy1Ia1VHgvBRN2qiaC1S/ewNry97kffEyxvj2RFzxCITGEFbguURCijrCER3LydyjQGvyCi30qKTbcSt1lB3adf3CrQft3WE7qb1lQSrAONMa2hoOMa74IUrX0bSddl1mwllrdYRturXbXs1Iw1o6//gxJE3Gltyd7YfzMGLlDlM2ow1f0tbHGrXt1UHMWCippHrooXbwcpDnLMHeJJhlsW9/nXGbSbl7q2iWzRjgsi89NZn0VNfun6LpGjJkCC+99BL33nsvw4cPZ82aNV6DyJqQl5fH+++/z6233sqll17qcfyaa65h0aJF/Oc//6F79+5MnDiRGTNmcODAAfr378/x48dZtmwZ8+bNw2Qy8dhjj3HTTTdhMpkYN24cWms+/vhjbrrpJrp3787KlSu54oor+PLLL7ngggtqpUxCiNrXNSWG5ft2SqAqqkTGqIpaNeCcBJJrcEbSUwUlTH/7e/6U9QNHukyEGNcA7Vdbc96xXsxJ7bvL8afW88i29nfdWXgS48IbiD7wORGb3mTvkocAiC486HH+AMNm3jL/g9vWDoJXLqXw+G9MMX1QYb5bK9flhdupg/RS2wHN7U5Baqk+hu2co8qDZGue70D1j6ZsHjTNo6vaXbbvasPnPB/0HJ1/fQ3evJLcg7tIJpdXzP/mTtO7PoNUALOyVtqlGOBu08JK05SKM8kkCv7Kd2tR9bb0kxDOxo4dy6OPPsr8+fMZNWoU69atY8mSJbVyryVLllBQUMCNN97o9fgNN9zAyZMnWbFiBQCvvvoqDzzwAK+//jqXX345d999NxER5RPvTZkyhaysLDZu3MjYsWOZPHkyO3fuJCEhAQCbzYbVaq10mR0hRP3WJSWRM7JEjagiFajKv3fv3nr9+vUBubeoWwdOFrBw/V5SYsOIDjUz7a2a+dw7J0ey/PbeZC1ZyhM/GMrGsYK9BfOL4Ds9zrmv5GYWWi/DhIWfQqdi1t7XMT2iEkkaOAXW/LNG8gowq2QK86xDuMb4Gf8yvwzAOlsXeqttGJXn3+FdxX8g2zYQgC/HltAyx/tMsKVO61AuK/o3x4hmRdD9pBrKZ++1GYMxWP2fyOAPxXeywubaetFV7SbDuIqdugVvWYewI8T7TJ7evJdyH1dOfdCvtEqp77TWvtfcaWCqWtet3HKIW/5XPsnV4NQk5k7qUxtZazR++uknUlNTA50NIVxU9nvZ2Oo6ti7VnPR/1njRtGitmfL6j/SfODPQWRF1KCLEREbf1mc9MFm6/opa1yImlD8N7lS2/fbNFzD1jfWu3XjPwrbDp1m6OZdfw7pzit0ux/bpRN6z9uNK41qX/d/a7BMmWTCxw9yZ1OLNXq+dpI/WaJAK8IjpDfbqJB4yla8XeIHhZ5/pnwp6kfCSQuZZB6MraFEtFakKGGpcz1pbqkuQClQpSAVooVwnboomj8ygR4lS9qV1gvEe4PsSbZAWVX/lu3X9DQuSaloIIUTDppQipIrPDkJI119R5y7qkMCfBp/j8/gjo7uy8aGh9God4zNNqWdW/VI+wZKbx0oyKNLla07usSWyy2nZj5fMEyGyZsdKnNHBdC58gzuKZ3gcMyjNm0GPE+kI9vzxV/PrDDd8i/Iy4683Aw0/MsppCR1/OS8HBNBSHSeSfP5sWsgjptf5t/nFsiAV4E+mxVW6fqTB/zI3ZUUWK7OWuH55Eh4sgaoQQoiGLxhZokZUjQSqot5plxBOdKiZmVekkhhZ8fjWPbn5fL/nhNdj+0nkjpIZHNVRHNBxPGCZRunkRABfFrWHu7bC7BM8mbqgRvL+me08ighit665iW6uNn6Owc9A9WLDj9xs9LGWaQV+sLl+cdBcHedB0zzuMC1houkj0o0/uBwPVlX7VjQCCVT98cpnO8lzG6MaLmNUhRBCNALhJhsWi7SqCv9JoCoCwupjbHTruDAu6mCfRKN32zi+un8QrWJDK7zW9sOea52W+tDWhz5FL3FR0XN8aTvX5diJ/BJsKDAY+M2WzL9KxlWxFJ7W2lKZOqAde3RSta9VaojxO9Qp38vfOAtXRYSrqn9j+b12DVRbqmOMMK6r8nV8CdMSqPpjw17PZXyax1T8+y+EEEI0BJ2aR3HsgH/PM0KABKoiQFrHhXnsm35ZBxbeeiFGQ3mrp9loIDrU7JG26jzHcVttmlMF9m/2Dv9eyFbdptp3+drWleSoYEKjEqp8bok28q2tk9djzfZ/6LL9sbXnWeXPlx9sHV22uxt2VamLcmVC9Zkau1Zj5t6aCjDqvBYByIkQQghRs9JaxnB8X8XL+QnhTAJVERBD05qREFG+QP19wztz77AuNIsO8UgbYq69ro/Hz9jX9zxyuoifbJ6B6o3F93NX8R8YWPQUN4S9WOG1DulYftEtiQwxkxAZwhrruV7TLbJczAZbe4/9O3QLlrovm+NFvg7m9pI/Ma5oNqsqCFjXWM/lSEi7Sq8H8JtOxqrPelK2SgVb82vt2o2J+0RK795+UaXd34UQQoiGoFNKInn7twc6G6IBkUBVBESQyUD27f2ZflkHHht7Lrdd3MFn2tBqBKr92sdVeDz3TDFaaw7/XshB4lhrK19K4CPr+Xxu6062bSB7dTJnItrwWexYr9cp0mYeLpkIKCKCTSRGBvO4JYOfbSkc01HYtOKUDmOFtQ+zLZNZbu3ncY2fdWuyrJfx15LrsVUQNK61pVKMmW91F6aW3MuLliu9psu0DmJDdLrLvj22RK9pLZg4QqzPe1bJJf/HSnWRyy6zxXf3bFHujFuLalRITfQmEEIIIQIvJjIMW773eUWE8EamkxQBkxIXxr3DulSa7mxbVBMjg5lx2Tms3el7rOXxvCLyiiyOlizFH4tnMNH0EYU6iP9Zh7ikjQk183XyVGKP/0Cq2sMW3ZZNtnYc1HG8Y72kLNCLCDGREBHEJ7otw4sfc5ztGni+YR1Of8MWLjVuLNv3ufVcLJiYax1Bph7CSvPdtFTHPfK8xtbdZft964X8wfSey758HcxqWw+SY+JIP/UuxsJcAOZZB3OfYQEmbB7XPaDjaa5yfb5X/vrzjvNYW9CS46ZgzhBCHqHc3ju98hMFZ4rdJlIKlomUhBBCNB4hVZyMUTRtEqiKei+0irOePnFNd4osNtJTk1BexqY6m79uD+0Sw8u2jxLLk5ZrvaaNCQvCFBHNqOK/EUwxRQR5TRcZbCIhorS7pvf7l2Biask93GJbzmDjd3xp68pSW3m3X1NwOFcVPMpNphUeQehntvNctrfotmzvdhedNj9Vtu99az8KCeaEimbHsLdYu/gZduiWZFkHcUvQhyTo8oDUou0dK/K17y6m1tj2GE/s9HncWfavNjQJPGC5GYAgo4E7zx/u17lN3Zki166/sjSNEKImKaXGAXOAVKCv1nq9j3S7gdOAFbBorXvXVR5F4yaBqqgKeQoS9V6IqWo91M9vE0v7xAgALFbPlkNnX+w4xm3/+86v60aHmssmdvIVpIK9RdWfcYVWjLxoHcWL1lGe1wg2sb8ghsctGWy1teEp838wKRvzLens0p5rvxZecCe0a8vpT5/ji5OxPGK5EYBii40DoZ15yDKlLO2C2FuZnvuPsu05lkkAnCTCaz5P61BCp38L2gLL/gibFgLwq605rdRRgpVrK6B2G1EQFWpGqdob/9pYaK09WlTDanF8thCiSdoMjAVe9iPtZVpr/9ZGE8JPMSGKwvw8QsK8P3MI4UzGqIp6r6otqsFOD/cmY+W/4ruP+zfRT2xYEFGhFX+3kxARTPuECKcW1bMT4dSS9p7tIi4seo70oid40DLVa/rwEDOcP5m1l+fwh5K7yMM+q3KJ1caJ/GKXtDsSBkHXMdiMwXxi7UG2dQAAOdYLvF77DeswTCYTmENgzMtMLr6P8UV/Ib34SUYU/90l7TvWiz3Oj67kPRN2BSVWnFdtCjEb/Pr9FQ3fyJEjOfdc75OvAcyYMYPY2FiKivxbemrHjh0opfjggw/K9rVq1Yr777+/wvM2bNiAUoovvvjCv4w7vPTSSyxbtsxjvz/3rA0fffQRSikuu+yyOr93fae1/klrvS3Q+RBNV1rLGA7v2x3obIgGQp6CRL1X1cmU3FtgL+nkfQKhqooJM1c4uc1FHeJ5/rqeBJkM1Z6pNSLENbg7Siy/6pY+04cH2dMHuZW9yGIj94xroBoVHgbj3mDnrTu5qeQ+zmBfp/NDWx/esV7MaR3KR9Ze3Fp8F9cXP8CBnneXn2wwcChpIOu0fdKpHboVL1lGYtOKX2wt2gkcIwAAHxpJREFUecEy2iNvNbO8UOPn0e03SAL8piIjI4PNmzezZcsWj2NWq5V33nmHsWPHEhx89vXKe++9x/Tp06uTTZ98Baq1ec+KZGZmArBmzRr2799f5/dvJDSwUin1nVLqlkBnRjQeqa3iOLX/l0BnQzQQEqiKes/XZEqXdvYegAa7pb93WGfaJYQTEWwivUvSWecjJsxMlI+ga2yvlrx9cz/6tY8HqHaLalXHJoY5Jt0xG1272HprUY0Nt3dbdl6vFsCGgXtKbuPcorncXHIPH9r6MGrMdTx6VTeXdBMvbFv2emhaMmva/JH2RfMZUvxPr92SJVD1T77HREoSqDYVo0ePJiwsjKysLI9jq1ev5vDhw2RkZFTrHj179iQlJaVa12gI9ywqKiI7O5v09HRsNhsLFy6s0/vXB0qpj5VSm738eH6T6Ft/rXUv4HJgulLKs7uM/V63KKXWK6XWv7LwQ29JhHDRsVUCpw/8GuhsiAZCAlVR7/nq+uurpTTYrVWxW8toVt9zKZsfHsYT487zaHX0V0xYkM+gyz0wTaxmoBpZ1UDVEZy7l73YYiP3jOvEBXGOQLVlTChBXruW2gPYsT1bMr5Pa4/up9dd0JoVdw5kwS39eOmG82keHepynjsJVP2T57Y0TVgVu7yLhisiIoKRI0eyYMECj2NZWVkkJyeXdWPdv38/U6ZMoV27doSGhtKpUyceeughSkoqnqDEWzfc5557jpSUFMLDwxk9ejSHDh3yOO+JJ56gd+/eREVFkZyczOjRo/n11/KHzAEDBrBx40ZeffVVlFIopZg3b57Pe2ZlZdGtWzeCg4Np3bo1s2fPxmot700wd+5clFJs2bKFwYMHEx4eTmpqKkuXLq3kXbRbsWIFJ0+eZObMmfTp06esddXd4sWL6dOnD6GhoSQkJDBixAj27t1bdnzjxo2MGDGC6OhoIiMj6devH5988olfeQg0rfVgrXU3Lz/+vYn2axxw/HsEyAb6+kj3ita6t9a69y3XDquZAohGLTjIjMkia6sL/8hX9qLeKw2s3HVrGe2xz6DAZPA9cU9ceBBPj+/By5/9ysZ9p6qUj5hQ311/3fNY2VhWZ4mRwRw97Tr2LKKKgWppMGl2CypLrJoTbl1/Y8PseQ0yGXhkdFdmL91CsZdJpyoK6FObR5W9bhZdcVAugap/7EsklZMW1WqY41k3BMQc/+uYjIwMFi5cyHfffcf5558PQElJCdnZ2Vx//fUYjfYvLo4ePUpCQgJPP/00MTEx/Pzzzzz88MMcO3aMF154we/7LV68mDvuuIPp06dz5ZVXsnr1am6++WaPdPv27eOOO+6gdevWnDp1ihdffJEBAwawfft2IiMjeeWVV7jqqqtITU3lgQceAKBjx45e75mTk0NGRgZTpkzhX//6Fxs2bGD27Nnk5uby/PPPe7wft9xyC/fddx9PP/0048ePZ9euXTRv7tlrw1lmZibNmjXj0ksvJSMjgz//+c/s2LHDJU9vvPEGU6ZM4frrr+ehhx7CZrOxatUqjh07RkpKClu2bKF///6kpaXx8ssvExcXx/r169mzZ4/f729DppQKBwxa69OO10OBRwKcLdGIhCAz/wr/yJOQqPf6tYv3uv+cJM8Z44JMhkpnmL3i3OZccW5zrDZN+pOf+j2Zkr3rr/c/mXi3QLUqs9y2jgvzDFRD/P/T7JESU/baPbgsttjIdev66xxUT+jbmrG9WjHq+S/4+dBpl3TurbO+NIsKqfB4SlyYX9dp6txbVCVQbVouv/xyYmJiyMrKKgtUP/zwQ3Jzc126/fbo0YMePXqUbffv35/Q0FBuu+02nnnmGfvEZ37429/+xsiRI8sCxGHDhnH48GHeeOMNl3TPPPNM2Wur1cqQIUNITEzkvffe47rrriMtLY2wsDASExPp169fhfecPXs2gwcP5rXXXgNg+PDh2Gw2Zs+ezYMPPugShN5zzz1MnDixrMzNmjVj+fLlTJs2zef18/LyeP/995k6dSoGg4Hx48dzzz33kJWVxaxZs8rKcP/99zNu3Liyll+AUaPKZ1+fM2cOcXFxrFmzhpAQe/02dOjQCsvWUCilxgDPAYnAcqXUBq31MKVUC2Cu1voKIBnIdvw/ZgLe1lp/4POiQlRRsCpBay0rAohK+fUkqpQarpTappTaoZTymMJPKXWxUup7pZRFKXVNzWdTNGWt48O8Bk0xYZ4trYUlFS9H48xoUDw4Io3SejIhIoipA9r5TB8TGuSzpTM+wjMvGX3Lx2a1jAllw+whPDOhh0e6FjGhHvsqC1Jiwsy0TwwnrXkUD4/qWrbfs0XVxkn3Mapu71uQyeD1fv52kU6uJFAd1aOFX9dp6vI9JlOSrr9NSXBwMGPGjGHhwoVox/TPCxYsoE2bNi4BoM1m48knnyQ1NZXQ0FDMZjOTJk2ioKCAffv2+XWv4uJiNm7cyOjRrkMWx44d65H2q6++YvDgwcTHx2MymQgPDyc/P5/t27dXqXwlJSVs2LCBcePGuewfP348VquVtWvXuux3DgyTkpJISEiotHxLly4lPz+fCRMmANCiRQsGDhzo0v1369atHD58mClTpvi6DJ988gkZGRllQWpjorXO1lq30loHa62TtdbDHPsPOIJUtNY7tdbnOX66aq3/Fthci8amRUwwp08eD3Q2RANQ6ZOoUsoIvIB9QH0akKGUSnNLtgeYDLxd0xkUAlxbDZ1Vd9KiIWnJvHPbRTwyuivv/XEAfxmZxlPjz/NIZ1AQGWLCZDR4DVbjwj3z8ZeRafxxUEeuu6A1b97Ul5iwIEb38Jy51701FiAiuOIg5cL28Xxy96Xk3DmQ85xbVI3eZv31PkbVmdHLt5qla9FWplm074e5e4d1Jimy8T3s1YYz0qLa5GVkZLBnzx6+/vprCgsLWbp0KRkZGS6tDk8++ST/93//x7hx41i2bBnffPMNzz77LACFhYV+3efIkSPYbDaSklwnl3Pf3rVrF8OGDcNoNPLKK6/w5Zdf8u233xIXF+f3vZzvabVaSU5Odtlfup2bm+uyPybGtc4PCgqq9J6ZmZm0aNGC1NRUTp48ycmTJ7nyyivZunUrP/74IwDHj9sfjivqQnzixIlKuxgLIc5et1bRHN6zM9DZEA2AP09CfYEdWuudAEqpLGA0sLU0gdZ6t+OY/81ZQlTBhL4prNtV/iBzoWN23eSoYI7l+be2oC/nt4nl/DaxZdvO4y9LRYeaMTjGvkaHmj26aXoLNsOCTNw9tHOl9/cW6EUEVzyu01vAC56toPtPFnikiQnzvPY3u3M99o3o7t+Dmq9AdOA5CRW2UAtXZ9xn/ZUW1bNXhbGh9cmgQYNITk4mKyuLgwcPcvr0aY/ZfhctWsSECRN45JHyIYOlQZi/kpKSMBgMHDlyxGW/+/aKFSsoKipiyZIlhIbae34UFxdz8uTJKt2v9J5Go9HjHocPHwYgLi6uytd0lpuby8qVKykpKfF6rczMTLp37058vP3/joMHD7p0oXYWGxvLwYMHq5UfIYRvXVonsvTb7XCe1zm6hCjjT9++lsBep+19jn1C1JmR3VvQpVlk2fa43q2Ayrudng1vk/84dzOO9DJ+1FvXX18u79as7HVUiMnrMjsVjVE9r1U06anel9lx7/rrLjzI6HW5H/egtE/b2ArXjHXWLDrEpVV3SFoyn993GW9M6etzaSHhSSZTEkajkXHjxrFo0SLefvttUlNT6d69u0uagoICj/VU58+fX6X7BAUF0b17d4+ZdN99912PexmNRpdxr1lZWdhsrt9J+9PaaTab6dmzJ4sWLXLZv3DhQoxGY6XjWyvzzjvvUFJSwrx581i9erXLT3p6OllZWWitSUtLo1mzZrz55ps+r1Wavqioel+CCiG8S0mKIf/o3soTiibPnychbyOd9dnczLFo9C0ArVu3PptLiCbKbDTw7u0X8dHWw7SKDStrAa2rQNV5n7fB/2FB/gcVM69IpaDESu6ZYu4a3IlwL+d6G5O7dHp/lLK3+PoKSCsbV1pk8d7pYVDnJJb/aG9BiAw28cQ1nt2fK/L65D68/uUuQsxGpvRvW6X3Q9jJZEoC7N1/n3/+ebKzs11aTUsNGTKEF198kd69e9O+fXveeustdu/eXeX7zJw5k2uvvZYZM2YwatQoVq9ezccff+ySJj09nfvuu48pU6YwZcoUNm3axFNPPUVUlGuvky5durB69WpWrlxJXFwc7du399qq+fDDDzNixAimTZvGuHHj2LhxI3PmzOG2226rdlfbzMxMunXrxvXXX+9x7MiRI4wfP561a9dy4YUX8vjjjzNp0iSCgoIYP348AKtWreLGG2+kZ8+ePPzww/Tt25dLLrmEu+66i/j4eL7//nuSk5OZNGkSVquV4OBgHnnkEWbOnFmtfAvRFBkMBoK1fBEkKudPi+o+wHnF7lbAgbO5mfN6W4mJ3tfAFMKXsCATo3u0dOmme1EH1xmBEyOrN2YVINRLK6DzPouXpVyqIiUujDem9GXZjAFc1iXJa9DprTtz91bRdG8VU2GrqdlY8Qx6vpaKGdOzJU+NP4+bB7bjf9MuoG1CeCWlcBUXHsTdQzsz/bKOEqSepXxZR1UAF154IW3btkVrXTYpkLOHH36Ya6+9lpkzZ5KRkUF4eDhPPfVUle8zbtw4nn76abKzs7nqqqvYtGkT//3vf13S9OjRg1dffZWvvvqKkSNHsnDhQhYvXkxkZKRLutmzZ9OpUyfGjRtHnz59yMnJ8XrPK664grfffpu1a9dy5ZVX8uyzz3Lfffe5zCx8Ng4ePMiaNWu48cYbvR4fNWoUUVFRvP22fRqNiRMnsmjRIjZv3szYsWOZNGkSv/zyC6XPJampqXz++efExMQwdepUxo4dS3Z2dtkX7FprrFarR8uyEMJ/wUqWqBGV8+eJ8lvgHKVUO2A/MAG4rlZzJYSfLu/WjPaJ4ew8egawT95TXd5aTJ13WWxn1aHAp+SoYNonhLPzmL0M/TvG08HLREb+TOPuPpmSu4s6JnjdbzAoxvRsxZiefmRY1Io891l/pUW1SVJKsWvXLp/HIyMjvXZbLZ0pGOzrmDpvA15nzL3zzju58847fV4HYPLkyUyePLnCa3Xs2JFVq1Z5XN/bPTMyMjzG3TqbNm2a1yVoKprxt3nz5litVp/HQ0JCOHXKddzyNddcwzXX+F6koEePHnzwgfcVWUwmk8f7JISomhBlwWa1YjDKl7LCt0qfhLTWFqXUDOBDwAi8prXeopR6BFivtV6mlOoDZAOxwJVKqYe11l0ruKwQNcJkNLB0en9yNh0kJS6Mizp4D8Sqy+AUJBb76D57tpRSvHB9L574cBtBRgMPjkileXSIS/DqbVkbX9fyJSEiiGkyuVG9le8xmZIEqkIIIRqnc5pFcvTwfhJbyFBA4ZtfT0Ja6xwgx23fbKfX32LvEixEnYsMMTO+T+1WdK4tqjXf3Su1eRSvTe7jsi97en9W/XSYNvFhnN/m7GfEPC8lhrkTexMaZPS5DqywU0oNB57B/qXcXK31Y27HJwNPYO9dAvC81npuTdzbc4yqfMsshBCicUprFc3ivb9KoCoq5M8YVSGEk+mXdXTZvql/7bRSRoeaGdurVbWCVIB28WEkRgZLkFoJP9eMBligte7h+KmRIBVk1l8hhBBNR+eUJE4f+CXQ2RD1nASqQnhxQTvX4PDybuUzUl7VsyWdku1jSFvGhDJtYP3uTtsmvmoTIzVhZWtGa62LgdI1o+vEGfcWVen6K4QQopGKjw7H8vvRQGdD1HPyJCSEF/cN78INc9dRUGKlbXwYY3uVLx0cFWJm2YwB7MnNp2VMaL1v+eqQ5Dkxk/DK25rRF3hJd7VS6mJgO3CX1rpGFoM74z5GVbr+VonW2q8Jx4SoCzLZkhAVU0oRoooDnQ1Rz9XvJ2whAuT8NrGsvOtifj2aR992cYS4LVkTYjbSKTnSx9mBNTQtmZVbDwMQFWIivUtSgHPUYPizZvR7QKbWukgpdRvwJjDI40JnsWZ0vtusv7LMj//MZjMFBQWEhYUFOitCAFBQUIDZ7H05MCGEXTASqIqKyZOQED6kxIWREtfwHnxnjUijoMTK8bxi7h7aqd63+NYjla4ZrbU+7rT5X+BxbxfSWr8CvALQu3dvv5pWmkWHEGQykFdk4UyRRcYUV0FSUhL79++nZcuWhIaGSsuqCBitNQUFBezfv5/k5ORAZ0eIei0qCIqLCgkKDgl0VkQ9JU9CQjQyrePD+N9Ubz1WRSUqXTNaKdVca33QsTkK+Kmmbr78joFlr6XbYNVERUUBcODAAUpKZBF5EVhms5nk5OSy30shhHepLWP4ed9vtOrQOdBZEfWUBKpCCIF/a0YDdyilRgEWIBeYXBt5kRbBqouKipLAQAghGpC0VrGs3fuLBKrCJwlUhRDCwY81ox8AHqjrfAkhhBCNTcdWCZxetyPQ2RD1mCxPI4QQQgghhKhT4aHBGIrzAp0NUY9JoCqEEEIIIYSoc8G6KNBZEPWYBKpCCCGEEEKIOidL1IiKSKAqhBBCCCGEqHOJkWbO/H4y0NkQ9ZRMpiSEEEIIIaonJAbCCwOdC9HA9D23M1uLTpEQmRTorIhaEGquXqipArVen1LqKPBbFU5JAI7VUnbqIylv4ybl9a2N1jqxNjNTl6Suq5SUt3GT8vrWqOq6+kApdYvW+hXJg+RB8lC/8nC2AhaoVpVSar3Wuneg81FXpLyNm5RX+NLU3ispb+Mm5RV1qT68/5IHyYPkoebIGFUhhBBCCCGEEPWKBKpCCCGEEEIIIeqVhhSoNsi+1dUg5W3cpLzCl6b2Xkl5Gzcpr6hL9eH9lzzYSR7sJA/V0GDGqAohhBBCCCGEaBoaUouqEEIIIYQQQogmoEEEqkqp4UqpbUqpHUqp+wOdn5qmlNqtlNqklNqglFrv2BenlPpIKfWL49/YQOezOpRSrymljiilNjvt81pGZfes4/P+USnVK3A5Pzs+yjtHKbXf8TlvUEpd4XTsAUd5tymlhgUm12dHKZWilFqtlPpJKbVFKXWnY3+j/XxrS2Ov66Dx13dS10ld15g+3/pOKTXO8VnYlFI+ZzX1Vu8EIA+1Vr/7W4cqpaxOf5fLaujeFZZLKRWslFrgOL5OKdW2Ju5bxTxMVkoddSr7tBq+v0c96Ha81usCP/JwqVLqlNN7MLuG73+JUkorpS532tfOkadnz/rCWut6/QMYgV+B9kAQsBFIC3S+ariMu4EEt33/BO53vL4feDzQ+axmGS8GegGbKysjcAWwAlBAP2BdoPNfQ+WdA9zjJW2a4/c6GGjn+H03BroMVShrc6CX43UksN1Rpkb7+dbS+9jo6zpHORt1fSd1ndR1jenzre8/QCrQGfgU6F1BOo96py7zUNv1u791KJBXw2WvtFzA7cBLjtcTgAUByMNk4Pla/D30qAfdjtd6XeBHHi4F3q+t98Bxj0+Arxyvo4EtwPvVqecbQotqX2CH1nqn1roYyAJGBzhPdWE08Kbj9ZvAVQHMS7VprdcAuW67fZVxNPCWtlsLxCilmtdNTmuGj/L6MhrI0loXaa13ATuw/943CFrrg1rr7x2vTwM/AS1pxJ9vLWmqdR00ovpO6roKSV3XwD7f+k5r/ZPWelsDyENt1++BqkP9KZdz3t4B0pVSqo7zUKv8qAdrvS6oYl1cWx4CLlRKDQUWAiXABK219Wwv2BAC1ZbAXqftfY59jYkGViqlvlNK3eLYl6y1Pgj2/xyBpIDlrvb4KmNj/sxnOLp9vObUNafRlNfRpacnsI6m+flWR1N5X5pifdcU/xakrmtE5W0EvNU7dam2fxf8rUNDlFLrlVJrlVI1Ecz6U66yNFprC3AKiK+Be1clDwBXO+qkd5RSKTV4f3/Ul7rgQqXURqXUCqVU15q+uNb6c+BjIBvoBozUWueVHldKvegYFuL3TL6mms5kLfD2rUtjm6q4v9b6gFIqCfhIKfVzoDMUYI31M38ReBR7WR4FngRuopGUVykVASwG/qS1/r2CL0wbRXlrQVN5X6S+K9dYP3Op6xxJvexrcOUNNKXUx0AzL4ce1Fov9fMyHvWOowWqrvJQ7d+FivJQhcu0drwP7YFPlFKbtNa/ViUf7tnyss+9XLX9d+DP9d8DMrXWRUqp27C38A6qwTxUpj7UBd8DbbTWeco+b8AS4JxauM8OYDBwp9Z6n9uxTOxDQw75e7GGEKjuA5y/+WgFHAhQXmqF1vqA498jSqls7N0YDiulmmutDzq6BxwJaCZrh68yNsrPXGt9uPS1Uuq/2PvtQyMor1LKjP3Bbb7W+l3H7ib1+daAJvG+NNH6rkn9LUhd17g/37qmtR5cA9fwVu/4HajWQB6q/btQUR6UUn7VoU7vw06l1KfYewVUJ1D1p1ylafYppUzYxy7WZBfVSvOgtT7utPlf4PEavL8/Al4XaK1/d3qdo5T6j1IqQWt9rKbu4eitcBP2ccLTgLlueVjjSOf3NRtC199vgXMcM0cFYR+IXSMzldUHSqlwpVRk6WtgKLAZexknOZJNAvz91rAh8VXGZcBExyxp/YBTpV1aGjK38QhjsH/OYC/vBGWfGa8d9m+4vqnr/J0tx1iTV4GftNb/djrUpD7fGtCo6zpo0vVdk/pbkLqucX++DU0F9U5dqu36vdI6VCkVq5QKdrxOAPoDW6t5X3/K5Zy3a4BPtNY12ZpYaR7c6qRR2MeX16WA1wVKqWaOOgylVF/sMeDxis+q0vWHAM8DNwO3ARcopxmAz5q3GZbq2w/22bK2Y//W58FA56eGy9Ye+zcPG7HPjvWgY388sAr4xfFvXKDzWs1yZgIHsQ+s3gdM9VVG7F0kXnB83puoYCa/+vrjo7z/c5TnR+yVVnOn9A86yrsNuDzQ+a9iWQdg78LyI7DB8XNFY/58a/G9bLR1naN8jb6+k7pO6rrG9PnW9x/sX4TsA4qAw8CHjv0tgBzHa6/1Tl3mwbFda/V7Bb+DvYG5jtcXOX4PNzr+nVpD9/YoF/AIMMrxOgRYhL1L6DdA+1r4PagsD/9wfPYbgdVAlxq+v7d68DbgNsfxWq8L/MjDDKf3YC1wUQ3euytwEvir076PgG98pNf+Xls5ThBCCCGEEEIIIfziGPe9DlgPXKtLI3OlLgY+wz6h0nK3c7TW2q/+vxKoCiGEEEIIIYSodVUJVBvCGFUhhBBCCCGEEA2UUmquUmqf4/U+pdTcSs+RFlUhhBBCCCGEEPWJtKgKIYQQQgghhKhXJFAVQgghhBBCCFGvSKAqKqSUmqOU0j5+bghAfrRSakZd31cI0bhJXSeEEELUL6ZAZ0A0CKeA4V7276jrjAghRC2Suk4IIYSoJyRQFf6waK3XBjoTQghRy6SuE0IIIeoJ6forqkUp1dbRRe06pdT/lFKnlVJHlFIPeUk7SCm1TilVqJQ6rJT6j1Iqwi1NvFLqZaXUQUe6bUqpP7ldyqiU+rtS6qjjXi8opYKdrhHjmAL7gOMae5RS/62lt0AI0QRIXSeEEELULWlRFX5RSnn8rmitLU6bTwDvA9cAFwMPKaWOaa1fcJyfBnwAfARcDaQAjwHtcXS1U0qFAp8CScDDwM9AR8ePs7uBT4AbgO7AP4DfgH86jv8buAi4CzjkuNfFZ1t2IUTTIXWdEEIIUT/IOqqiQkqpOYBHi4FDO8e/u4CPtNZDnc77L3AFkKK1timlsoDzgS5aa6sjzbXAAuAirfXXSqlbgReBXlrrDT7yo4HPtdYXO+1bAjTTWvdzbG8GXtZaP3e25RZCNC1S1wkhhBD1i7SoCn+cAgZ72X8AaOF4ne127F1gGtAK2AP0Bd4pfXBzWAxYgAHA18Ag4AdfD25OVrptbwV6O21vAO5VSlmBj7XW2yu5nhBCgNR1QgghRL0hY1SFPyxa6/Vefoqd0hxxO6d0u7nTv4edEzge5I4DcY5d8cBBP/Jz0m27GAhx2p4BLAFmA9uUUr8opSb4cV0hRNMmdZ0QQghRT0igKmpKko/tg07/uqRRShmxP7DlOnYdp/xh76xprU9qre/QWjcDzgPWAfMdY8eEEKI6pK4TQggh6oAEqqKmjHHbHov9gW2fY3sdMMbxwOacxgR84dheBfRUSnWvqUxprX8E7sX+u96lpq4rhGiypK4TQggh6oCMURX+MCml+nnZv9fpdVel1MvYx2JdDEwF7tRa2xzH/wr8ACxRSr2IfTzX48CHWuuvHWneAqYDKx0Tm2zDPolJJ631/f5mVin1BfZxZJsBDdwMnAG+8fcaQogmSeo6IYQQop6QQFX4Ixr7BCDu/gLMc7y+DxiJ/eGtEHgUeL40odZ6i1LqcuDv2Ccf+R3IdJxXmqZQKTUI+1IOjwBRwG7gP1XM79fAZKAtYMX+0Hi51npfBecIIYTUdUIIIUQ9IcvTiGpRSrXFvmTDlVrr9wObGyGEqB1S1wkhhBB1S8aoCiGEEEIIIYSoVyRQFUIIIYQQQghRr0jXXyGEEEIIIYQQ9Yq0qAohhBBCCCGEqFckUBVCCCGEEEIIUa9IoCqEEEIIIYQQol6RQFUIIYQQQgghRL0igaoQQgghhBBCiHpFAlUhhBBCCCGEEPXK/wNYFKIZEhVK7wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1152x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tf.random.set_seed(1)\n",
    "\n",
    "model = tf.keras.Sequential([\n",
    "    NoisyLinear(4, noise_stddev=0.1),\n",
    "    tf.keras.layers.Dense(units=4, activation='relu'),\n",
    "    tf.keras.layers.Dense(units=4, activation='relu'),\n",
    "    tf.keras.layers.Dense(units=1, activation='sigmoid')])\n",
    "\n",
    "model.build(input_shape=(None, 2))\n",
    "model.summary()\n",
    "\n",
    "## compile:\n",
    "model.compile(optimizer=tf.keras.optimizers.SGD(),\n",
    "              loss=tf.keras.losses.BinaryCrossentropy(),\n",
    "              metrics=[tf.keras.metrics.BinaryAccuracy()])\n",
    "\n",
    "## train:\n",
    "hist = model.fit(x_train, y_train, \n",
    "                 validation_data=(x_valid, y_valid), \n",
    "                 epochs=200, batch_size=2, \n",
    "                 verbose=0)\n",
    "\n",
    "## Plotting\n",
    "history = hist.history\n",
    "\n",
    "fig = plt.figure(figsize=(16, 4))\n",
    "ax = fig.add_subplot(1, 3, 1)\n",
    "plt.plot(history['loss'], lw=4)\n",
    "plt.plot(history['val_loss'], lw=4)\n",
    "plt.legend(['Train loss', 'Validation loss'], fontsize=15)\n",
    "ax.set_xlabel('Epochs', size=15)\n",
    "\n",
    "ax = fig.add_subplot(1, 3, 2)\n",
    "plt.plot(history['binary_accuracy'], lw=4)\n",
    "plt.plot(history['val_binary_accuracy'], lw=4)\n",
    "plt.legend(['Train Acc.', 'Validation Acc.'], fontsize=15)\n",
    "ax.set_xlabel('Epochs', size=15)\n",
    "\n",
    "ax = fig.add_subplot(1, 3, 3)\n",
    "plot_decision_regions(X=x_valid, y=y_valid.astype(np.integer),\n",
    "                      clf=model)\n",
    "ax.set_xlabel(r'$x_1$', size=15)\n",
    "ax.xaxis.set_label_coords(1, -0.025)\n",
    "ax.set_ylabel(r'$x_2$', size=15)\n",
    "ax.yaxis.set_label_coords(-0.025, 1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "Readers may ignore the next cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[NbConvertApp] Converting notebook ch14_part1.ipynb to script\n",
      "[NbConvertApp] Writing 19996 bytes to ch14_part1.py\n"
     ]
    }
   ],
   "source": [
    "! python ../.convert_notebook_to_script.py --input ch14_part1.ipynb --output ch14_part1.py"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
